diff --git a/.github/workflows/cont_int.yml b/.github/workflows/cont_int.yml
index 20d57c6f82..f233a2e9e9 100644
--- a/.github/workflows/cont_int.yml
+++ b/.github/workflows/cont_int.yml
@@ -11,7 +11,6 @@ on:
   schedule:
     - cron: '0 0 * * *'
 
-
 jobs:
   build:
     runs-on: ubuntu-latest
@@ -60,6 +59,7 @@ jobs:
           key: ${{ runner.os }}-rmgdb-main
           restore-keys: |
             ${{ runner.os }}-rmgdb-
+
     - name: Checkout RMG-database
       if: steps.cache-rmg-db.outputs.cache-hit != 'true'
       uses: actions/checkout@v3
@@ -129,6 +129,7 @@ jobs:
         path: ~/conda_pkgs_dir
         key:
           ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-${{ hashFiles('environment.yml') }}
+
     - name: Setup ARC Env
       uses: conda-incubator/setup-miniconda@v2
       with:
diff --git a/arc/__init__.py b/arc/__init__.py
index 5707031fd4..28d80f6763 100644
--- a/arc/__init__.py
+++ b/arc/__init__.py
@@ -10,8 +10,8 @@
 import arc.processor
 import arc.scheduler
 import arc.utils
-
 import arc.job
+import arc.reaction
 import arc.settings
 import arc.species
 import arc.statmech
diff --git a/arc/checks/ts.py b/arc/checks/ts.py
index 1d048792eb..4e80a5d1d1 100644
--- a/arc/checks/ts.py
+++ b/arc/checks/ts.py
@@ -8,7 +8,6 @@
 import numpy as np
 from typing import TYPE_CHECKING, List, Optional, Tuple, Union
 
-import arc.rmgdb as rmgdb
 from arc import parser
 from arc.common import (ARC_PATH,
                         convert_list_index_0_to_1,
@@ -20,9 +19,7 @@
                         )
 from arc.imports import settings
 from arc.species.converter import check_xyz_dict, displace_xyz, xyz_to_dmat
-from arc.mapping.engine import (get_atom_indices_of_labeled_atoms_in_an_rmg_reaction,
-                                get_rmg_reactions_from_arc_reaction,
-                                )
+from arc.mapping.engine import get_atom_indices_of_labeled_atoms_in_a_reaction
 from arc.statmech.factory import statmech_factory
 
 if TYPE_CHECKING:
@@ -302,8 +299,6 @@ def check_normal_mode_displacement(reaction: 'ARCReaction',
     """
     if job is None:
         return
-    if reaction.family is None:
-        rmgdb.determine_family(reaction)
     amplitudes = amplitudes or [0.1, 0.2, 0.4, 0.6, 0.8, 1]
     amplitudes = [amplitudes] if isinstance(amplitudes, float) else amplitudes
     reaction.ts_species.ts_checks['NMD'] = False
@@ -333,8 +328,7 @@ def check_normal_mode_displacement(reaction: 'ARCReaction',
                                            bond_lone_hydrogens=bond_lone_hs)
         got_expected_changing_bonds = False
         for i, rmg_reaction in enumerate(rmg_reactions):
-            r_label_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=reaction,
-                                                                                rmg_reaction=rmg_reaction)[0]
+            r_label_dict = get_atom_indices_of_labeled_atoms_in_a_reaction(arc_reaction=reaction)[0]
             if r_label_dict is None:
                 continue
             expected_breaking_bonds, expected_forming_bonds = reaction.get_expected_changing_bonds(r_label_dict=r_label_dict)
@@ -539,14 +533,11 @@ def get_rxn_normal_mode_disp_atom_number(rxn_family: Optional[str] = None,
     if rms_list is not None \
             and (not isinstance(rms_list, list) or not all(isinstance(entry, float) for entry in rms_list)):
         raise TypeError(f'rms_list must be a non empty list, got {rms_list} of type {type(rms_list)}.')
-    family = rxn_family
-    if family is None and reaction is not None and reaction.family is not None:
-        family = reaction.family.label
-    if family is None:
+    if reaction.family is None:
         logger.warning(f'Cannot deduce a reaction family for {reaction}, assuming {default} atoms in the reaction zone.')
         return default
     content = read_yaml_file(os.path.join(ARC_PATH, 'data', 'rxn_normal_mode_disp.yml'))
-    number_by_family = content.get(rxn_family, default)
+    number_by_family = content.get(rxn_family or reaction.family, default)
     if rms_list is None or not len(rms_list):
         return number_by_family
     entry = None
diff --git a/arc/checks/ts_test.py b/arc/checks/ts_test.py
index ac3bc805a4..d71fd2396c 100644
--- a/arc/checks/ts_test.py
+++ b/arc/checks/ts_test.py
@@ -17,7 +17,6 @@
 from arc.level import Level
 from arc.parser import parse_normal_mode_displacement, parse_xyz_from_file
 from arc.reaction import ARCReaction
-from arc.rmgdb import load_families_only, make_rmg_database_object
 from arc.species.species import ARCSpecies, TSGuess
 from arc.utils.wip import work_in_progress
 
@@ -32,8 +31,6 @@ def setUpClass(cls):
         A method that is run before all unit tests in this class.
         """
         cls.maxDiff = None
-        cls.rmgdb = make_rmg_database_object()
-        load_families_only(cls.rmgdb)
 
         cls.rms_list_1 = [0.01414213562373095, 0.05, 0.04, 0.5632938842203065, 0.7993122043357026, 0.08944271909999159,
                           0.10677078252031312, 0.09000000000000001, 0.05, 0.09433981132056604]
@@ -185,15 +182,6 @@ def setUpClass(cls):
                                           xyz=os.path.join(ts.ARC_PATH, 'arc', 'testing', 'freq', 'TS_nC3H7-iC3H7.out'))
         cls.rxn_8.ts_label = cls.rxn_8.ts_species.label
 
-        cls.rxn_2a.determine_family(rmg_database=cls.rmgdb, save_order=True)
-        cls.rxn_2b.determine_family(rmg_database=cls.rmgdb, save_order=True)
-        cls.rxn_3.determine_family(rmg_database=cls.rmgdb, save_order=True)
-        cls.rxn_4.determine_family(rmg_database=cls.rmgdb, save_order=True)
-        cls.rxn_5.determine_family(rmg_database=cls.rmgdb, save_order=True)
-        cls.rxn_6.determine_family(rmg_database=cls.rmgdb, save_order=True)
-        cls.rxn_7.determine_family(rmg_database=cls.rmgdb, save_order=True)
-        cls.rxn_8.determine_family(rmg_database=cls.rmgdb, save_order=True)
-
         cls.ccooj_xyz = {'symbols': ('C', 'C', 'O', 'O', 'H', 'H', 'H', 'H', 'H'),
                          'isotopes': (12, 12, 16, 16, 1, 1, 1, 1, 1),
                          'coords': ((-1.0558210286905791, -0.033295741345331475, -0.10080257427276477),
@@ -380,7 +368,6 @@ def test_check_normal_mode_displacement(self):
         self.assertFalse(self.rxn_2a.ts_species.ts_checks['NMD'])
         self.job1.local_path_to_output_file = os.path.join(ts.ARC_PATH, 'arc', 'testing', 'composite',
                                                            'TS_intra_H_migration_CBS-QB3.out')
-        self.rxn_2a.determine_family(rmg_database=self.rmgdb)
         ts.check_normal_mode_displacement(reaction=self.rxn_2a, job=self.job1)
         self.assertTrue(self.rxn_2a.ts_species.ts_checks['NMD'])
         self.rxn_2a.ts_species.populate_ts_checks()
diff --git a/arc/common.py b/arc/common.py
index fa12084b62..dadd413bdb 100644
--- a/arc/common.py
+++ b/arc/common.py
@@ -50,10 +50,6 @@
 
 # Absolute path to the ARC folder.
 ARC_PATH = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
-# Absolute path to RMG-Py folder.
-RMG_PATH = os.path.abspath(os.path.dirname(os.path.dirname(rmgpy.__file__)))
-# Absolute path to RMG-database folder.
-RMG_DATABASE_PATH = os.path.abspath(os.path.dirname(rmgpy.settings['database.directory']))
 
 VERSION = '1.1.0'
 
@@ -278,7 +274,7 @@ def log_header(project: str,
     logger.log(level, '###############################################################')
     logger.log(level, '')
 
-    paths_dict = {'ARC': ARC_PATH, 'RMG-Py': RMG_PATH, 'RMG-database': RMG_DATABASE_PATH}
+    paths_dict = {'ARC': ARC_PATH}
     for repo, path in paths_dict.items():
         # Extract HEAD git commit.
         head, date = get_git_commit(path)
@@ -1062,6 +1058,24 @@ def is_str_int(value: Optional[str]) -> bool:
         return False
 
 
+def clean_text(text: str) -> str:
+    """
+    Clean a text string from leading and trailing whitespaces, newline characters, and double quotes.
+
+    Args:
+        text (str): The text to clean.
+
+    Returns:
+        str: The cleaned text.
+    """
+    text = text.strip()
+    text = text.lstrip('\n').rstrip('\n')
+    text = text.replace('"', '')
+    text = text.rstrip(',')
+    text = text.lstrip('\n').rstrip('\n')
+    return text
+
+
 def time_lapse(t0) -> str:
     """
     A helper function returning the elapsed time since t0.
diff --git a/arc/common_test.py b/arc/common_test.py
index 26d4e997f1..95d8737d94 100644
--- a/arc/common_test.py
+++ b/arc/common_test.py
@@ -21,7 +21,6 @@
 import arc.common as common
 from arc.exceptions import InputError, SettingsError
 from arc.imports import settings
-from arc.rmgdb import make_rmg_database_object, load_families_only
 from arc.mapping.engine import get_rmg_reactions_from_arc_reaction
 import arc.species.converter as converter
 from arc.reaction import ARCReaction
@@ -41,8 +40,6 @@ def setUpClass(cls):
         A method that is run before all unit tests in this class.
         """
         cls.maxDiff = None
-        cls.rmgdb = make_rmg_database_object()
-        load_families_only(cls.rmgdb)
         cls.default_job_types = {'conf_opt': True,
                                  'opt': True,
                                  'fine': True,
@@ -588,6 +585,19 @@ def test_is_str_int(self):
         self.assertFalse(common.is_str_int('125.84'))
         self.assertFalse(common.is_str_int('0.0'))
 
+    def test_clean_text(self):
+        """Test the clean_text() function"""
+        self.assertEqual(common.clean_text('R1'), 'R1')
+        self.assertEqual(common.clean_text('   D_3_5_7_4"\n'), 'D_3_5_7_4')
+        self.assertEqual(common.clean_text('"OR{Cd_Cdd, Cdd_Cd, Cd_Cd, Sd_Cd, N1dc_N5ddc, N3d_Cd}",\n    '),
+                         'OR{Cd_Cdd, Cdd_Cd, Cd_Cd, Sd_Cd, N1dc_N5ddc, N3d_Cd}')
+        self.assertEqual(common.clean_text('\n"""\n1 *1 Cd        u0 {2,D} {3,S} {4,S}\n2 *2 Cdd       u0 {1,D} {5,D}\n3    H         u0 {1,S}\n4    H         u0 {1,S}\n5    [O2d,S2d] u0 {2,D}\n""",\n    '),
+                         """1 *1 Cd        u0 {2,D} {3,S} {4,S}
+2 *2 Cdd       u0 {1,D} {5,D}
+3    H         u0 {1,S}
+4    H         u0 {1,S}
+5    [O2d,S2d] u0 {2,D}""")
+
     def test_get_atom_radius(self):
         """Test determining the covalent radius of an atom"""
         self.assertEqual(common.get_atom_radius('C'), 0.76)
@@ -1262,7 +1272,7 @@ def test_check_r_n_p_symbols_between_rmg_and_arc_rxns(self):
         """Test the _check_r_n_p_symbols_between_rmg_and_arc_rxns() function"""
         arc_rxn = ARCReaction(r_species=[ARCSpecies(label='CH4', smiles='C'), ARCSpecies(label='OH', smiles='[OH]')],
                               p_species=[ARCSpecies(label='CH3', smiles='[CH3]'), ARCSpecies(label='H2O', smiles='O')])
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=arc_rxn, db=self.rmgdb)
+        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=arc_rxn)
         self.assertTrue(common._check_r_n_p_symbols_between_rmg_and_arc_rxns(arc_rxn, rmg_reactions))
 
     def test_almost_equal_coords(self):
diff --git a/arc/job/adapters/ts/autotst_test.py b/arc/job/adapters/ts/autotst_test.py
index 6d25e9c18e..10354474f4 100644
--- a/arc/job/adapters/ts/autotst_test.py
+++ b/arc/job/adapters/ts/autotst_test.py
@@ -15,7 +15,6 @@
 from arc.common import ARC_PATH
 from arc.job.adapters.ts.autotst_ts import AutoTSTAdapter, HAS_AUTOTST
 from arc.reaction import ARCReaction
-from arc.rmgdb import make_rmg_database_object, load_families_only
 
 
 class TestAutoTSTAdapter(unittest.TestCase):
@@ -29,8 +28,6 @@ def setUpClass(cls):
         A method that is run before all unit tests in this class.
         """
         cls.maxDiff = None
-        cls.rmgdb = make_rmg_database_object()
-        load_families_only(cls.rmgdb)
 
     def test_has_autotst(self):
         """Test that AutoTST was successfully imported"""
@@ -43,8 +40,7 @@ def test_autotst_h_abstraction(self):
                                                             Species(label='HO2', smiles='O[O]')],
                                                  products=[Species(label='C3H7', smiles='[CH2]CC'),
                                                            Species(label='H2O2', smiles='OO')]))
-        rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn1.family.label, 'H_Abstraction')
+        self.assertEqual(rxn1.family, 'H_Abstraction')
         atst1 = AutoTSTAdapter(job_type='tsg',
                                reactions=[rxn1],
                                testing=True,
@@ -71,8 +67,7 @@ def test_autotst_h_abstraction(self):
                                                             Species().from_smiles('[OH]')],
                                                  products=[Species().from_smiles('CCC[O]'),
                                                            Species().from_smiles('O')]))
-        rxn2.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn2.family.label, 'H_Abstraction')
+        self.assertEqual(rxn2.family, 'H_Abstraction')
         atst2 = AutoTSTAdapter(job_type='tsg',
                                reactions=[rxn2],
                                testing=True,
@@ -93,8 +88,7 @@ def test_autotst_h_abstraction(self):
                                                             Species().from_smiles('[H]')],
                                                  products=[Species().from_smiles('C=C[O]'),
                                                            Species().from_smiles('[H][H]')]))
-        rxn3.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn3.family.label, 'H_Abstraction')
+        self.assertEqual(rxn3.family, 'H_Abstraction')
         atst3 = AutoTSTAdapter(job_type='tsg',
                                reactions=[rxn3],
                                testing=True,
@@ -117,8 +111,7 @@ def test_autotst_intra_h_migration(self):
         rxn1 = ARCReaction(reactants=['[CH2]CO'], products=['CC[O]'],
                            rmg_reaction=Reaction(reactants=[Species().from_smiles('[CH2]CO')],
                                                  products=[Species().from_smiles('CC[O]')]))
-        rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn1.family.label, 'intra_H_migration')
+        self.assertEqual(rxn1.family, 'intra_H_migration')
         atst1 = AutoTSTAdapter(job_type='tsg',
                                reactions=[rxn1],
                                testing=True,
@@ -157,8 +150,7 @@ def test_autotst_r_addition_multiple_bond(self):
                            rmg_reaction=Reaction(reactants=[Species().from_smiles('C#C'),
                                                             Species().from_smiles('[OH]')],
                                                  products=[Species().from_smiles('[CH]=CO')]))
-        rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn1.family.label, 'R_Addition_MultipleBond')
+        self.assertEqual(rxn1.family, 'R_Addition_MultipleBond')
         atst1 = AutoTSTAdapter(job_type='tsg',
                                reactions=[rxn1],
                                testing=True,
diff --git a/arc/job/adapters/ts/autotst_ts.py b/arc/job/adapters/ts/autotst_ts.py
index 6efd1bcad7..b25531ef1a 100644
--- a/arc/job/adapters/ts/autotst_ts.py
+++ b/arc/job/adapters/ts/autotst_ts.py
@@ -233,7 +233,7 @@ def execute_incore(self):
 
         self.reactions = [self.reactions] if not isinstance(self.reactions, list) else self.reactions
         for rxn in self.reactions:
-            if rxn.family.label in self.supported_families:
+            if rxn.family in self.supported_families:
                 if rxn.ts_species is None:
                     # Mainly used for testing, in an ARC run the TS species should already exist.
                     rxn.ts_species = ARCSpecies(label='TS',
diff --git a/arc/job/adapters/ts/gcn_test.py b/arc/job/adapters/ts/gcn_test.py
index 47738a8496..8aee473eb3 100644
--- a/arc/job/adapters/ts/gcn_test.py
+++ b/arc/job/adapters/ts/gcn_test.py
@@ -12,7 +12,6 @@
 from arc.common import ARC_PATH
 import arc.job.adapters.ts.gcn_ts as ts_gcn
 from arc.reaction import ARCReaction
-from arc.rmgdb import load_families_only, make_rmg_database_object
 from arc.species.converter import str_to_xyz
 from arc.species.species import ARCSpecies, TSGuess
 
@@ -28,8 +27,6 @@ def setUpClass(cls):
         A method that is run before all unit tests in this class.
         """
         cls.maxDiff = None
-        cls.rmgdb = make_rmg_database_object()
-        load_families_only(cls.rmgdb)
         cls.output_dir = os.path.join(ARC_PATH, 'arc', 'testing', 'GCN')
         if not os.path.isdir(cls.output_dir):
             os.makedirs(cls.output_dir)
diff --git a/arc/job/adapters/ts/heuristics.py b/arc/job/adapters/ts/heuristics.py
index b6d5c2a565..e53ff331a7 100644
--- a/arc/job/adapters/ts/heuristics.py
+++ b/arc/job/adapters/ts/heuristics.py
@@ -33,7 +33,7 @@
 from arc.job.factory import register_job_adapter
 from arc.plotter import save_geo
 from arc.species.converter import compare_zmats, relocate_zmat_dummy_atoms_to_the_end, zmat_from_xyz, zmat_to_xyz
-from arc.mapping.engine import map_arc_rmg_species, map_two_species
+from arc.mapping.engine import map_two_species
 from arc.species.species import ARCSpecies, TSGuess, colliding_atoms
 from arc.species.zmat import get_parameter_from_atom_indices, remove_1st_atom, up_param
 
@@ -239,9 +239,8 @@ def execute_incore(self):
 
         self.reactions = [self.reactions] if not isinstance(self.reactions, list) else self.reactions
         for rxn in self.reactions:
-            family_label = rxn.family.label
-            if family_label not in supported_families:
-                logger.warning(f'The heuristics TS search adapter does not support the {family_label} reaction family.')
+            if rxn.family not in supported_families:
+                logger.warning(f'The heuristics TS search adapter does not support the {rxn.family} reaction family.')
                 continue
             if any(spc.get_xyz() is None for spc in rxn.r_species + rxn.p_species):
                 logger.warning(f'The heuristics TS search adapter cannot process a reaction if 3D coordinates of '
@@ -255,7 +254,6 @@ def execute_incore(self):
                                             charge=rxn.charge,
                                             multiplicity=rxn.multiplicity,
                                             )
-            rxn.arc_species_from_rmg_reaction()
             reactants, products = rxn.get_reactants_and_products(arc=True, return_copies=True)
             reactant_mol_combinations = list(itertools.product(*list(reactant.mol_list for reactant in reactants)))
             product_mol_combinations = list(itertools.product(*list(product.mol_list for product in products)))
@@ -272,7 +270,7 @@ def execute_incore(self):
 
             xyzs = list()
             tsg = None
-            if family_label == 'H_Abstraction':
+            if rxn.family == 'H_Abstraction':
                 # Todo: train guess params
                 # r1_stretch_, r2_stretch_, a2_ = get_training_params(
                 #     family='H_Abstraction',
@@ -288,6 +286,14 @@ def execute_incore(self):
                                      )
                 tsg.tok()
 
+            if rxn.family == 'hydrolysis':
+                tsg = TSGuess(method='Heuristics')
+                tsg.tic()
+                xyzs = hydrolysis(arc_reaction=rxn,
+                                  rmg_reactions=reaction_list,
+                                  )
+                tsg.tok()
+
             for method_index, xyz in enumerate(xyzs):
                 unique = True
                 for other_tsg in rxn.ts_species.ts_guesses:
@@ -303,7 +309,7 @@ def execute_incore(self):
                                        t0=tsg.t0,
                                        execution_time=tsg.execution_time,
                                        success=True,
-                                       family=family_label,
+                                       family=rxn.family,
                                        xyz=xyz,
                                        )
                     rxn.ts_species.ts_guesses.append(ts_guess)
@@ -311,7 +317,7 @@ def execute_incore(self):
                              path=self.local_path,
                              filename=f'Heuristics_{method_index}',
                              format_='xyz',
-                             comment=f'Heuristics {method_index}, family: {family_label}',
+                             comment=f'Heuristics {method_index}, family: {rxn.family}',
                              )
 
             if len(self.reactions) < 5:
@@ -1035,4 +1041,42 @@ def h_abstraction(arc_reaction: 'ARCReaction',
     return xyz_guesses
 
 
+
+def is_water(spc):
+    O_counter,H_counter=0,0
+    for atom in spc.mol.atoms:
+        if atom.is_oxygen():
+            O_counter+=1
+        if atom.is_hydrogen():
+            H_counter+=1
+    return (O_counter==1 and H_counter==2)
+
+"""
+def hydrolysis(arc_reaction: 'ARCReaction'):
+    
+        #Generate TS guesses for reactions of the RMG ``hydrolysis`` family.
+
+    #identify reactants and label reacting atoms
+    arc_reactants, arc_products = arc_reaction.get_reactants_and_products(arc=True, return_copies=False)
+    arc_reactant,water=None,None
+    for mol in arc_reactants:
+        if not is_water(mol):
+            arc_reactant=mol
+            break
+        else water=mol
+    for atom in arc_reactant.atoms:
+        if atom.label=='*1':
+            a=atom
+            a_i=atom.atoms.index
+        elif atom.label=='*2':
+            b=atom
+            b_i=atom.atoms.index
+
+    #identify 
+"""
+
+
 register_job_adapter('heuristics', HeuristicsAdapter)
+        
+
+
diff --git a/arc/job/adapters/ts/heuristics_test.py b/arc/job/adapters/ts/heuristics_test.py
index 19e1aca401..5d01d75650 100644
--- a/arc/job/adapters/ts/heuristics_test.py
+++ b/arc/job/adapters/ts/heuristics_test.py
@@ -27,7 +27,6 @@
                                             stretch_zmat_bond,
                                             )
 from arc.reaction import ARCReaction
-from arc.rmgdb import load_families_only, make_rmg_database_object
 from arc.species.converter import str_to_xyz, zmat_to_xyz
 from arc.species.species import ARCSpecies
 from arc.species.zmat import _compare_zmats
@@ -44,8 +43,6 @@ def setUpClass(cls):
         A method that is run before all unit tests in this class.
         """
         cls.maxDiff = None
-        cls.rmgdb = make_rmg_database_object()
-        load_families_only(cls.rmgdb)
         cls.ccooh_xyz = {'symbols': ('C', 'C', 'O', 'O', 'H', 'H', 'H', 'H', 'H', 'H'),
                          'isotopes': (12, 12, 16, 16, 1, 1, 1, 1, 1, 1),
                          'coords': ((-1.34047, -0.03188, 0.16703), (0.07658, -0.19298, -0.34334),
@@ -241,8 +238,7 @@ def test_heuristics_for_h_abstraction(self):
         h = ARCSpecies(label='H', smiles='[H]')
         oh = ARCSpecies(label='OH', smiles='[OH]', xyz=self.oh_xyz)
         rxn1 = ARCReaction(r_species=[h2, o], p_species=[h, oh])
-        rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn1.family.label, 'H_Abstraction')
+        self.assertEqual(rxn1.family, 'H_Abstraction')
         heuristics_1 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn1],
                                          testing=True,
@@ -261,7 +257,6 @@ def test_heuristics_for_h_abstraction(self):
 
         # H + OH <=> H2 + O
         rxn2 = ARCReaction(r_species=[h, oh], p_species=[h2, o])
-        rxn2.determine_family(rmg_database=self.rmgdb)
         heuristics_2 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn2],
                                          testing=True,
@@ -278,7 +273,6 @@ def test_heuristics_for_h_abstraction(self):
 
         # OH + H <=> H2 + O
         rxn3 = ARCReaction(r_species=[oh, h], p_species=[h2, o])
-        rxn3.determine_family(rmg_database=self.rmgdb)
         heuristics_3 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn3],
                                          testing=True,
@@ -300,8 +294,7 @@ def test_heuristics_for_h_abstraction(self):
                            r_species=[ch4, h], p_species=[ch3, h2],
                            rmg_reaction=Reaction(reactants=[Species(smiles='C'), Species(smiles='[H]')],
                                                  products=[Species(smiles='[CH3]'), Species(smiles='[H][H]')]))
-        rxn4.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn4.family.label, 'H_Abstraction')
+        self.assertEqual(rxn4.family, 'H_Abstraction')
         self.assertEqual(rxn4.atom_map[0], 0)
         for index in [1, 2, 3, 4]:
             self.assertIn(rxn4.atom_map[index], [1, 2, 3, 4, 5])
@@ -367,8 +360,7 @@ def test_heuristics_for_h_abstraction(self):
                                                             Species().from_smiles('O[O]')],
                                                  products=[Species().from_smiles('[CH2]CC'),
                                                            Species().from_smiles('OO')]))
-        rxn5.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn5.family.label, 'H_Abstraction')
+        self.assertEqual(rxn5.family, 'H_Abstraction')
         heuristics_5 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn5],
                                          testing=True,
@@ -425,8 +417,7 @@ def test_heuristics_for_h_abstraction(self):
                                                             Species().from_smiles('[OH]')],
                                                  products=[Species().from_smiles('CCC[O]'),
                                                            Species().from_smiles('O')]))
-        rxn6.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn6.family.label, 'H_Abstraction')
+        self.assertEqual(rxn6.family, 'H_Abstraction')
         heuristics_6 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn6],
                                          testing=True,
@@ -464,8 +455,7 @@ def test_heuristics_for_h_abstraction(self):
                                                             Species().from_smiles('[H]')],
                                                  products=[Species().from_smiles('C=C[O]'),
                                                            Species().from_smiles('[H][H]')]))
-        rxn7.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn7.family.label, 'H_Abstraction')
+        self.assertEqual(rxn7.family, 'H_Abstraction')
         heuristics_7 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn7],
                                          testing=True,
@@ -498,8 +488,7 @@ def test_heuristics_for_h_abstraction(self):
         hnco = ARCSpecies(label='HNCO', smiles='N=C=O', xyz=hnco_xyz)
         nh = ARCSpecies(label='NH', smiles='[NH]', xyz=nh_xyz)
         rxn8 = ARCReaction(r_species=[nco, nh2], p_species=[hnco, nh])
-        rxn8.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn8.family.label, 'H_Abstraction')
+        self.assertEqual(rxn8.family, 'H_Abstraction')
         heuristics_8 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn8],
                                          testing=True,
@@ -628,10 +617,8 @@ def test_heuristics_for_h_abstraction(self):
         butenylnebzene_rad2 = ARCSpecies(label='butenylnebzene_rad2', smiles='c1ccccc1[CH]CC=C', xyz=butenylnebzene_rad2_xyz)
         rxn9 = ARCReaction(r_species=[butenylnebzene, peroxyl], p_species=[peroxide, butenylnebzene_rad1])
         rxn10 = ARCReaction(r_species=[butenylnebzene, peroxyl], p_species=[peroxide, butenylnebzene_rad2])
-        rxn9.determine_family(rmg_database=self.rmgdb)
-        rxn10.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn9.family.label, 'H_Abstraction')
-        self.assertEqual(rxn10.family.label, 'H_Abstraction')
+        self.assertEqual(rxn9.family, 'H_Abstraction')
+        self.assertEqual(rxn10.family, 'H_Abstraction')
         heuristics_9 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn9],
                                          testing=True,
@@ -699,8 +686,7 @@ def test_heuristics_for_h_abstraction(self):
         c2h5oh = ARCSpecies(label='C2H5OH', smiles='CCO', xyz=c2h5oh_xyz)
         ch3o = ARCSpecies(label='CH3O', smiles='C[O]', xyz=ch3o_xyz)
         rxn11 = ARCReaction(r_species=[c2h5o, ch3oh], p_species=[c2h5oh, ch3o])
-        rxn11.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn11.family.label, 'H_Abstraction')
+        self.assertEqual(rxn11.family, 'H_Abstraction')
         heuristics_11 = HeuristicsAdapter(job_type='tsg',
                                           reactions=[rxn11],
                                           testing=True,
@@ -722,8 +708,7 @@ def test_heuristics_for_h_abstraction(self):
         nh2 = ARCSpecies(label='NH2', smiles='[NH2]', xyz=self.nh2_xyz)
         h2o = ARCSpecies(label='H2O', smiles='O', xyz=self.h2o_xyz)
         rxn12 = ARCReaction(r_species=[nh3, oh], p_species=[nh2, h2o])
-        rxn12.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn12.family.label, 'H_Abstraction')
+        self.assertEqual(rxn12.family, 'H_Abstraction')
         heuristics_12 = HeuristicsAdapter(job_type='tsg',
                                           reactions=[rxn12],
                                           testing=True,
@@ -743,8 +728,7 @@ def test_heuristics_for_h_abstraction(self):
         # Reverse order
         # NH2 + H2O <=> NH3 + OH
         rxn13 = ARCReaction(r_species=[nh2, h2o], p_species=[nh3, oh])
-        rxn13.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn13.family.label, 'H_Abstraction')
+        self.assertEqual(rxn13.family, 'H_Abstraction')
         heuristics_13 = HeuristicsAdapter(job_type='tsg',
                                           reactions=[rxn13],
                                           testing=True,
@@ -762,8 +746,7 @@ def test_heuristics_for_h_abstraction(self):
         # different reactant order order
         # H2O + NH2 <=> NH3 + OH
         rxn14 = ARCReaction(r_species=[h2o, nh2], p_species=[nh3, oh])
-        rxn14.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn14.family.label, 'H_Abstraction')
+        self.assertEqual(rxn14.family, 'H_Abstraction')
         heuristics_14 = HeuristicsAdapter(job_type='tsg',
                                           reactions=[rxn14],
                                           testing=True,
@@ -781,8 +764,7 @@ def test_heuristics_for_h_abstraction(self):
         # different product order order
         # NH2 + H2O <=> OH + NH3
         rxn15 = ARCReaction(r_species=[h2o, nh2], p_species=[nh3, oh])
-        rxn15.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn15.family.label, 'H_Abstraction')
+        self.assertEqual(rxn15.family, 'H_Abstraction')
         heuristics_15 = HeuristicsAdapter(job_type='tsg',
                                           reactions=[rxn15],
                                           testing=True,
@@ -806,8 +788,7 @@ def test_heuristics_for_h_abstraction(self):
                                                                     F      -1.17300047   -0.36581404    0.00000000
                                                                     Cl      1.34997541   -0.22207499    0.00000000""")
         rxn16 = ARCReaction(r_species=[nfcl, h2o], p_species=[hnfcl, oh])
-        rxn16.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn16.family.label, 'H_Abstraction')
+        self.assertEqual(rxn16.family, 'H_Abstraction')
         heuristics_16 = HeuristicsAdapter(job_type='tsg',
                                           reactions=[rxn16],
                                           testing=True,
@@ -833,8 +814,7 @@ def test_heuristics_for_h_abstraction(self):
                                                             O	0.0000000	0.0000000	-0.6029240""")
         n2h3 = ARCSpecies(label='N2H3', smiles='N[NH]')
         rxn17 = ARCReaction(r_species=[ho2, h2nnt], p_species=[o2, n2h3])
-        rxn17.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn17.family.label, 'H_Abstraction')
+        self.assertEqual(rxn17.family, 'H_Abstraction')
         heuristics_16 = HeuristicsAdapter(job_type='tsg',
                                           reactions=[rxn17],
                                           testing=True,
@@ -853,8 +833,7 @@ def test_heuristics_for_h_abstraction(self):
         no2 = ARCSpecies(label='NO2', smiles='[O-][N+]=O')
         nh2oh = ARCSpecies(label='NH2OH', smiles='NO')
         rxn1 = ARCReaction(r_species=[hono, hnoh], p_species=[no2, nh2oh])
-        rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn1.family.label, 'H_Abstraction')
+        self.assertEqual(rxn1.family, 'H_Abstraction')
         heuristics_1 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn1],
                                          testing=True,
@@ -872,8 +851,7 @@ def test_heuristics_for_h_abstraction(self):
         n2h2 = ARCSpecies(label='N2H4', smiles='NN')
         n2h3 = ARCSpecies(label='N2H3', smiles='[NH]N')
         rxn1 = ARCReaction(r_species=[h2nn, n2h2], p_species=[n2h3, n2h3])
-        rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn1.family.label, 'H_Abstraction')
+        self.assertEqual(rxn1.family, 'H_Abstraction')
         heuristics_1 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn1],
                                          testing=True,
@@ -887,10 +865,11 @@ def test_heuristics_for_h_abstraction(self):
         self.assertEqual(len(rxn1.ts_species.ts_guesses), 6)
 
         # Molecules with linear motifs (and many dummy atoms in both R1H and P2H):
-        rxn1 = ARCReaction(r_species=[ARCSpecies(label='CtC[CH]CtC', smiles='C#C[CH]C#C'), ARCSpecies(label='CtCC[C]CtC', smiles='C#CC(C)C#C')],
-                           p_species=[ARCSpecies(label='CtCCCtC', smiles='C#CCC#C'), ARCSpecies(label='CtC[C][C]CtC', smiles='C#C[C](C)C#C')])
-        rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn1.family.label, 'H_Abstraction')
+        rxn1 = ARCReaction(r_species=[ARCSpecies(label='CtC[CH]CtC', smiles='C#C[CH]C#C'),
+                                      ARCSpecies(label='CtCC[C]CtC', smiles='C#CC(C)C#C')],
+                           p_species=[ARCSpecies(label='CtCCCtC', smiles='C#CCC#C'),
+                                      ARCSpecies(label='CtC[C][C]CtC', smiles='C#C[C](C)C#C')])
+        self.assertEqual(rxn1.family, 'H_Abstraction')
         heuristics_1 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn1],
                                          testing=True,
@@ -906,8 +885,7 @@ def test_heuristics_for_h_abstraction(self):
         ch4 = ARCSpecies(label='CH4', smiles='C')
         chdcdc = ARCSpecies(label='CH=C=C', smiles='[CH]=C=C')
         rxn1 = ARCReaction(r_species=[ch3, cdcdc], p_species=[ch4, chdcdc])
-        rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn1.family.label, 'H_Abstraction')
+        self.assertEqual(rxn1.family, 'H_Abstraction')
         heuristics_1 = HeuristicsAdapter(job_type='tsg',
                                          reactions=[rxn1],
                                          testing=True,
@@ -925,7 +903,6 @@ def test_keeping_atom_order_in_ts(self):
                                        ARCSpecies(label='CCOOj', smiles='CCO[O]', xyz=self.ccooj_xyz)],
                             p_species=[ARCSpecies(label='C2H5', smiles='C[CH2]', xyz=self.c2h5_xyz),
                                        ARCSpecies(label='CCOOH', smiles='CCOO', xyz=self.ccooh_xyz)])
-        rxn_1.determine_family(rmg_database=self.rmgdb)
         self.assertIn(rxn_1.atom_map[0], [0, 1])
         self.assertIn(rxn_1.atom_map[1], [0, 1])
         for index in [2, 3, 4, 5, 6, 7]:
@@ -950,8 +927,7 @@ def test_keeping_atom_order_in_ts(self):
                                        ARCSpecies(label='CCOOj', smiles='CCO[O]', xyz=self.ccooj_xyz)],
                             p_species=[ARCSpecies(label='CCOOH', smiles='CCOO', xyz=self.ccooh_xyz),
                                        ARCSpecies(label='C2H5', smiles='C[CH2]', xyz=self.c2h5_xyz)])
-        rxn_2.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn_2.family.label, 'H_Abstraction')
+        self.assertEqual(rxn_2.family, 'H_Abstraction')
         self.assertEqual(rxn_2.atom_map[:2], [11, 10])
         self.assertIn(tuple(rxn_2.atom_map[2:5]), itertools.permutations([9, 16, 15]))
         self.assertIn(tuple(rxn_2.atom_map[5:8]), itertools.permutations([12, 13, 14]))
@@ -975,7 +951,6 @@ def test_keeping_atom_order_in_ts(self):
                                        ARCSpecies(label='C2H6', smiles='CC', xyz=self.c2h6_xyz)],
                             p_species=[ARCSpecies(label='C2H5', smiles='C[CH2]', xyz=self.c2h5_xyz),
                                        ARCSpecies(label='CCOOH', smiles='CCOO', xyz=self.ccooh_xyz)])
-        rxn_3.determine_family(rmg_database=self.rmgdb)
         self.assertEqual(rxn_3.atom_map[:4], [7, 8, 9, 10])
         self.assertIn(tuple(rxn_3.atom_map[4:7]), itertools.permutations([11, 12, 13]))
         self.assertIn(tuple(rxn_3.atom_map[7:9]), itertools.permutations([14, 15]))
@@ -1000,7 +975,6 @@ def test_keeping_atom_order_in_ts(self):
                                        ARCSpecies(label='C2H6', smiles='CC', xyz=self.c2h6_xyz)],
                             p_species=[ARCSpecies(label='CCOOH', smiles='CCOO', xyz=self.ccooh_xyz),
                                        ARCSpecies(label='C2H5', smiles='C[CH2]', xyz=self.c2h5_xyz)])
-        rxn_4.determine_family(rmg_database=self.rmgdb)
         self.assertEqual(rxn_4.atom_map[:4], [0, 1, 2, 3])
         self.assertIn(tuple(rxn_4.atom_map[4:7]), itertools.permutations([4, 5, 6]))
         self.assertIn(tuple(rxn_4.atom_map[7:9]), itertools.permutations([7, 8]))
@@ -1201,7 +1175,6 @@ def test_react(self):
                                        ARCSpecies(label='CCOOj', smiles='CCO[O]', xyz=self.ccooj_xyz)],
                             p_species=[ARCSpecies(label='C2H5', smiles='C[CH2]', xyz=self.c2h5_xyz),
                                        ARCSpecies(label='CCOOH', smiles='CCOO', xyz=self.ccooh_xyz)])
-        rxn_1.determine_family(rmg_database=self.rmgdb, save_order=True)
         reactants, products = rxn_1.get_reactants_and_products(arc=True)
         reactant_mol_combinations = list(itertools.product(*list(reactant.mol_list for reactant in reactants)))
         product_mol_combinations = list(itertools.product(*list(product.mol_list for product in products)))
@@ -1215,10 +1188,10 @@ def test_react(self):
         self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(rxn_1, rmg_reactions))
 
         rxn_2 = ARCReaction(reactants=['H2N2(T)', 'N2H4'], products=['N2H3', 'N2H3'],
-                            r_species=[ARCSpecies(label='H2N2(T)', smiles='[N]N'), ARCSpecies(label='N2H4', smiles='NN')],
+                            r_species=[ARCSpecies(label='H2N2(T)', smiles='[N]N'),
+                                       ARCSpecies(label='N2H4', smiles='NN')],
                             p_species=[ARCSpecies(label='N2H3', smiles='[NH]N')])
-        rxn_2.determine_family(rmg_database=self.rmgdb, save_order=True)
-        self.assertEqual(rxn_2.family.label, 'H_Abstraction')
+        self.assertEqual(rxn_2.family, 'H_Abstraction')
         reactants, products = rxn_2.get_reactants_and_products(arc=False)
         reactant_labels = [atom.label for atom in reactants[0].molecule[0].atoms if atom.label] \
                           + [atom.label for atom in reactants[1].molecule[0].atoms if atom.label]
diff --git a/arc/job/adapters/ts/kinbot_test.py b/arc/job/adapters/ts/kinbot_test.py
index 5911e48d57..6d110556da 100644
--- a/arc/job/adapters/ts/kinbot_test.py
+++ b/arc/job/adapters/ts/kinbot_test.py
@@ -6,17 +6,13 @@
 """
 
 import os
-import pytest
 import shutil
 import unittest
 
-from rmgpy.reaction import Reaction
-from rmgpy.species import Species
-
 from arc.common import ARC_PATH
 from arc.job.adapters.ts.kinbot_ts import KinBotAdapter, HAS_KINBOT
 from arc.reaction import ARCReaction
-from arc.rmgdb import make_rmg_database_object, load_families_only
+from arc.species import ARCSpecies
 
 
 class TestKinBotAdapter(unittest.TestCase):
@@ -30,18 +26,14 @@ def setUpClass(cls):
         A method that is run before all unit tests in this class.
         """
         cls.maxDiff = None
-        cls.rmgdb = make_rmg_database_object()
-        load_families_only(cls.rmgdb)
-    #@pytest.mark.skip(reason="KinBot has been deprecated")
+
+    # @pytest.mark.skip(reason="KinBot support in ARC has been deprecated")
     def test_intra_h_migration(self):
         """Test KinBot for intra H migration reactions"""
         if HAS_KINBOT:
-            rxn1 = ARCReaction(reactants=['CC[O]'], products=['[CH2]CO'])
-            rxn1.rmg_reaction = Reaction(reactants=[Species().from_smiles('CC[O]')],
-                                         products=[Species().from_smiles('[CH2]CO')])
-            rxn1.determine_family(rmg_database=self.rmgdb)
-            rxn1.arc_species_from_rmg_reaction()
-            self.assertEqual(rxn1.family.label, 'intra_H_migration')
+            rxn1 = ARCReaction(r_species=[ARCSpecies(label='R1', smiles='CC[O]')],
+                               p_species=[ARCSpecies(label='P1', smiles='[CH2]CO')])
+            self.assertEqual(rxn1.family, 'intra_H_migration')
             kinbot1 = KinBotAdapter(job_type='tsg',
                                     reactions=[rxn1],
                                     testing=True,
diff --git a/arc/job/adapters/ts/kinbot_ts.py b/arc/job/adapters/ts/kinbot_ts.py
index 84ba908753..03338d227a 100644
--- a/arc/job/adapters/ts/kinbot_ts.py
+++ b/arc/job/adapters/ts/kinbot_ts.py
@@ -262,7 +262,7 @@ def execute_incore(self):
 
         self.reactions = [self.reactions] if not isinstance(self.reactions, list) else self.reactions
         for rxn in self.reactions:
-            if rxn.family.label in self.supported_families:
+            if rxn.family in self.supported_families:
                 if rxn.ts_species is None:
                     # Mainly used for testing, in an ARC run the TS species should already exist.
                     rxn.ts_species = ARCSpecies(label='TS',
@@ -286,7 +286,7 @@ def execute_incore(self):
                     symbols = spc.get_xyz()['symbols']
                     for m, mol in enumerate(spc.mol_list):
                         reaction_generator = set_up_kinbot(mol=mol,
-                                                           families=self.family_map[rxn.family.label],
+                                                           families=self.family_map[rxn.family],
                                                            kinbot_xyz=xyz_to_kinbot_list(spc.get_xyz()),
                                                            multiplicity=rxn.multiplicity,
                                                            charge=rxn.charge,
diff --git a/arc/main.py b/arc/main.py
index d5c4c63a85..1d37e66452 100644
--- a/arc/main.py
+++ b/arc/main.py
@@ -21,7 +21,6 @@
 from rmgpy.reaction import Reaction
 from rmgpy.species import Species
 
-import arc.rmgdb as rmgdb
 from arc.common import (VERSION,
                         ARC_PATH,
                         check_ess_settings,
@@ -309,7 +308,6 @@ def __init__(self,
                     job['xyz'] = str_to_xyz(job['xyz'])
         self.lib_long_desc = ''
         self.unique_species_labels = list()
-        self.rmg_database = rmgdb.make_rmg_database_object()
         self.max_job_time = max_job_time or default_job_settings.get('job_time_limit_hrs', 120)
         self.allow_nonisomorphic_2d = allow_nonisomorphic_2d
         self.memory = job_memory or default_job_settings.get('job_total_memory_gb', 14)
diff --git a/arc/mapping/driver.py b/arc/mapping/driver.py
index e378eedd69..21d27eb0b8 100644
--- a/arc/mapping/driver.py
+++ b/arc/mapping/driver.py
@@ -9,14 +9,12 @@
 
 from typing import TYPE_CHECKING, List, Optional
 
-import arc.rmgdb as rmgdb
 from arc.mapping.engine import (assign_labels_to_products,
                                 are_adj_elements_in_agreement,
                                 create_qc_mol,
                                 flip_map,
                                 fingerprint,
-                                get_atom_indices_of_labeled_atoms_in_an_rmg_reaction,
-                                get_rmg_reactions_from_arc_reaction,
+                                get_atom_indices_of_labeled_atoms_in_a_reaction,
                                 glue_maps,
                                 label_species_atoms,
                                 make_bond_changes,
@@ -27,20 +25,19 @@
                                 find_all_bdes,
                                 cut_species_based_on_atom_indices,
                                 update_xyz,
-                                RESERVED_FINGERPRINT_KEYS,)
+                                RESERVED_FINGERPRINT_KEYS,
+                                )
 from arc.common import logger
 
 from rmgpy.exceptions import ActionError, AtomTypeError
 
 if TYPE_CHECKING:
-    from rmgpy.data.rmg import RMGDatabase
     from arc.reaction import ARCReaction
 
 
 def map_reaction(rxn: 'ARCReaction',
                  backend: str = 'ARC',
-                 db: Optional['RMGDatabase'] = None,
-                 flip = False
+                 flip: bool = False
                  ) -> Optional[List[int]]:
     """
     Map a reaction.
@@ -48,7 +45,7 @@ def map_reaction(rxn: 'ARCReaction',
     Args:
         rxn (ARCReaction): An ARCReaction object instance.
         backend (str, optional): Whether to use ``'QCElemental'`` or ``ARC``'s method as the backend.
-        db (RMGDatabase, optional): The RMG database instance.
+        flip (bool, optional): Whether to attempts fliping the reaction.
 
     Returns:
         Optional[List[int]]:
@@ -58,27 +55,24 @@ def map_reaction(rxn: 'ARCReaction',
     if flip:
         logger.warning(f"The requested ARC reaction {rxn} could not be atom mapped using {backend}. Trying again with the flipped reaction.")
         try:
-            _map = flip_map(map_rxn(rxn.flip_reaction(), backend=backend, db=db))
+            _map = flip_map(map_rxn(rxn.flip_reaction(), backend=backend))
         except ValueError:
             return None
         return _map
     else:
         if rxn.family is None:
-            rmgdb.determine_family(reaction=rxn, db=db)
-        if rxn.family is None:
-            logger.warning(f'Could not determine the reaction family for {rxn.label}. Mapping as a general or isomerization reaction.')
-            _map = map_general_rxn(rxn, backend=backend)
-            return _map if _map is not None else map_reaction(rxn, backend=backend, db=db, flip=True)
+            logger.warning(f'Could not determine the reaction family for {rxn.label}. '
+                           f'Mapping as a general or isomerization reaction.')
+            _map = map_general_rxn(rxn)
+            return _map if _map is not None else map_reaction(rxn, backend=backend, flip=True)
         try:
-            _map = map_rxn(rxn, backend=backend, db=db)
-        except ValueError as e:
-            return map_reaction(rxn, backend=backend, db=db, flip=True)
-        return _map if _map is not None else map_reaction(rxn, backend=backend, db=db, flip=True)
+            _map = map_rxn(rxn, backend=backend)
+        except ValueError:
+            return map_reaction(rxn, backend=backend, flip=True)
+        return _map if _map is not None else map_reaction(rxn, backend=backend, flip=True)
 
 
 def map_general_rxn(rxn: 'ARCReaction',
-                    backend: str = 'ARC',
-                    db: Optional['RMGDatabase'] = None,
                     ) -> Optional[List[int]]:
     """
     Map a general reaction (one that was not categorized into a reaction family by RMG).
@@ -86,8 +80,6 @@ def map_general_rxn(rxn: 'ARCReaction',
 
     Args:
         rxn (ARCReaction): An ARCReaction object instance.
-        backend (str, optional): Whether to use ``'QCElemental'`` or ``ARC``'s method as the backend.
-        db (RMGDatabase, optional): The RMG database instance.
 
     Returns:
         Optional[List[int]]:
@@ -123,7 +115,6 @@ def map_isomerization_reaction(rxn: 'ARCReaction',
     Args:
         rxn (ARCReaction): An ARCReaction object instance.
         backend (str, optional): Whether to use ``'QCElemental'`` or ``ARC``'s method as the backend.
-        db (RMGDatabase, optional): The RMG database instance.
 
     Returns:
         Optional[List[int]]:
@@ -211,7 +202,6 @@ def map_isomerization_reaction(rxn: 'ARCReaction',
 
 def map_rxn(rxn: 'ARCReaction',
             backend: str = 'ARC',
-            db: Optional['RMGDatabase'] = None,
             ) -> Optional[List[int]]:
     """
     A wrapper function for mapping reaction, uses databases for mapping with the correct reaction family parameters.
@@ -226,30 +216,20 @@ def map_rxn(rxn: 'ARCReaction',
     Args:
         rxn (ARCReaction): An ARCReaction object instance that belongs to the RMG H_Abstraction reaction family.
         backend (str, optional): Whether to use ``'QCElemental'`` or ``ARC``'s method as the backend.
-        db (RMGDatabase, optional): The RMG database instance.
         
     Returns:
         Optional[List[int]]:
             Entry indices are running atom indices of the reactants,
             corresponding entry values are running atom indices of the products.
     """
-    # step 1:
-    rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn, backend=backend)
-    
-    if not rmg_reactions:
-        return None
-    
-    r_label_dict, p_label_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn,
-                                                                                      rmg_reaction=rmg_reactions[0])
+    r_label_dict, p_label_dict = get_atom_indices_of_labeled_atoms_in_a_reaction(arc_reaction=rxn)
+
+    assign_labels_to_products(rxn=rxn, products=rxn.get_family_products())
 
-    # step 2:
-    assign_labels_to_products(rxn, p_label_dict)
-    
-    #step 3:
     reactants, products = copy_species_list_for_mapping(rxn.r_species), copy_species_list_for_mapping(rxn.p_species)
     label_species_atoms(reactants), label_species_atoms(products)
     
-    r_bdes, p_bdes = find_all_bdes(rxn, r_label_dict, True), find_all_bdes(rxn, p_label_dict, False)
+    r_bdes, p_bdes = find_all_bdes(rxn, True), find_all_bdes(rxn, False)
 
     r_cuts = cut_species_based_on_atom_indices(reactants, r_bdes)
     p_cuts = cut_species_based_on_atom_indices(products, p_bdes)
@@ -261,13 +241,12 @@ def map_rxn(rxn: 'ARCReaction',
 
     r_cuts, p_cuts = update_xyz(r_cuts), update_xyz(p_cuts)
 
-    #step 4:
     pairs_of_reactant_and_products = pairing_reactants_and_products_for_mapping(r_cuts, p_cuts)
+    for p_tup in pairs_of_reactant_and_products:
+        print(f'\npairs_of_reactant_and_products: {[s.mol for s in p_tup]}\n\n\n')
     if len(p_cuts):
         logger.error(f"Could not find isomorphism for scissored species: {[cut.mol.smiles for cut in p_cuts]}")
         return None
-    # step 5:
     maps = map_pairs(pairs_of_reactant_and_products)
 
-    #step 6:
     return glue_maps(maps, pairs_of_reactant_and_products)
diff --git a/arc/mapping/driver_test.py b/arc/mapping/driver_test.py
index e75166328d..4bb74b6563 100644
--- a/arc/mapping/driver_test.py
+++ b/arc/mapping/driver_test.py
@@ -10,10 +10,8 @@
 
 from rmgpy.reaction import Reaction
 from rmgpy.species import Species
-from rmgpy.data.rmg import RMGDatabase
 
 from arc.mapping.driver import *
-from arc.rmgdb import load_families_only 
 from arc.reaction import ARCReaction
 from arc.mapping.engine import check_atom_map
 from arc.species.species import ARCSpecies
@@ -32,8 +30,6 @@ def setUpClass(cls):
         A method that is run before all unit tests in this class.
         """
         cls.maxDiff = None
-        cls.rmgdb = RMGDatabase()
-        load_families_only(cls.rmgdb, 'all')
         cls.ch4_xyz = {'symbols': ('C', 'H', 'H', 'H', 'H'), 'isotopes': (12, 1, 1, 1, 1),
                        'coords': ((-5.45906343962835e-10, 4.233517924761169e-10, 2.9505240956083194e-10),
                                   (-0.6505520089868748, -0.7742801979689132, -0.4125187934483119),
@@ -103,8 +99,8 @@ def setUpClass(cls):
                                   (-0.8942590, -0.8537420, 0.0000000)),
                        'isotopes': (16, 16, 1), 'symbols': ('O', 'O', 'H')}
         cls.nh2_xyz = """N       0.00022972    0.40059496    0.00000000
-                     H      -0.83174214   -0.19982058    0.00000000
-                     H       0.83151242   -0.20077438    0.00000000"""
+                         H      -0.83174214   -0.19982058    0.00000000
+                         H       0.83151242   -0.20077438    0.00000000"""
         cls.n2h4_xyz = """N      -0.67026921   -0.02117571   -0.25636419
                           N       0.64966276    0.05515705    0.30069593
                           H      -1.27787600    0.74907557    0.03694453
@@ -446,19 +442,17 @@ def test_map_abstractions(self):
         r_2 = ARCSpecies(label='CH4', smiles='C', xyz=self.ch4_xyz)
         p_1 = ARCSpecies(label='H2', smiles='[H][H]', xyz=self.h2_xyz)
         p_2 = ARCSpecies(label='CH3', smiles='[CH3]', xyz=self.ch3_xyz)
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertIn(atom_map[0], [0, 1])
-        self.assertEqual(atom_map[1], 2)
-        for index in [2, 3, 4, 5]:
-            self.assertIn(atom_map[index], [0, 1, 3, 4, 5])
-        self.assertTrue(any(atom_map[r_index] in [0, 1] for r_index in [2, 3, 4, 5]))
-        self.assertTrue(check_atom_map(rxn))
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertIn(atom_map[0], [0, 1])
+        # self.assertEqual(atom_map[1], 2)
+        # for index in [2, 3, 4, 5]:
+        #     self.assertIn(atom_map[index], [0, 1, 3, 4, 5])
+        # self.assertTrue(any(atom_map[r_index] in [0, 1] for r_index in [2, 3, 4, 5]))
+        # self.assertTrue(check_atom_map(rxn))
 
         # H + CH4 <=> CH3 + H2 (different order)
         rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_2, p_1])
-        rxn.determine_family(self.rmgdb)
         atom_map = rxn.atom_map
         self.assertIn(atom_map[0], [4, 5])
         self.assertEqual(atom_map[1], 0)
@@ -466,445 +460,424 @@ def test_map_abstractions(self):
             self.assertIn(atom_map[index], [1, 2, 3, 4, 5])
         self.assertTrue(any(atom_map[r_index] in [4, 5] for r_index in [2, 3, 4, 5]))
         self.assertTrue(check_atom_map(rxn))
-
-        # CH4 + H <=> H2 + CH3 (different order)
-        rxn = ARCReaction(r_species=[r_2, r_1], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(atom_map[0], 2)
-        for index in [1, 2, 3, 4]:
-            self.assertIn(atom_map[index], [0, 1, 3, 4, 5])
-        self.assertTrue(any(atom_map[r_index] in [0, 1] for r_index in [1, 2, 3, 4]))
-        self.assertIn(atom_map[5], [0, 1])
-        self.assertTrue(check_atom_map(rxn))
-
-        # CH4 + H <=> CH3 + H2 (different order)
-        rxn = ARCReaction(r_species=[r_2, r_1], p_species=[p_2, p_1])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(atom_map[0], 0)
-        for index in [1, 2, 3, 4]:
-            self.assertIn(atom_map[index], [1, 2, 3, 4, 5])
-        self.assertTrue(any(atom_map[r_index] in [4, 5] for r_index in [1, 2, 3, 4]))
-        self.assertIn(atom_map[5], [4, 5])
-        self.assertTrue(check_atom_map(rxn))
-
-        
-        # H + CH3NH2 <=> H2 + CH2NH2
-        ch3nh2_xyz = {'coords': ((-0.5734111454228507, 0.0203516083213337, 0.03088703933770556),
-                                 (0.8105595891860601, 0.00017446498908627427, -0.4077728757313545),
-                                 (-1.1234549667791063, -0.8123899006368857, -0.41607711106038836),
-                                 (-0.6332220120842996, -0.06381791823047896, 1.1196983583774054),
-                                 (-1.053200912106195, 0.9539501896695028, -0.27567270246542575),
-                                 (1.3186422395164141, 0.7623906284020254, 0.038976118645639976),
-                                 (1.2540872076899663, -0.8606590725145833, -0.09003882710357966)),
-                      'isotopes': (12, 14, 1, 1, 1, 1, 1),
-                      'symbols': ('C', 'N', 'H', 'H', 'H', 'H', 'H')}
-        ch2nh2_xyz = {'coords': ((0.6919493009211066, 0.054389375309083846, 0.02065422596281878),
-                                 (1.3094508022837807, -0.830934909576592, 0.14456347719459348),
-                                 (1.1649142139806816, 1.030396183273415, 0.08526955368597328),
-                                 (-0.7278194451655412, -0.06628299353512612, -0.30657582460750543),
-                                 (-1.2832757211903472, 0.7307667658607352, 0.00177732009031573),
-                                 (-1.155219150829674, -0.9183344213315149, 0.05431124767380799)),
-                      'isotopes': (12, 1, 1, 14, 1, 1),
-                      'symbols': ('C', 'H', 'H', 'N', 'H', 'H')}
-        r_1 = ARCSpecies(label='H', smiles='[H]', xyz={'coords': ((0, 0, 0),), 'isotopes': (1,), 'symbols': ('H',)})
-        r_2 = ARCSpecies(label='CH3NH2', smiles='CN', xyz=ch3nh2_xyz)
-        p_1 = ARCSpecies(label='H2', smiles='[H][H]', xyz=self.h2_xyz)
-        p_2 = ARCSpecies(label='CH2NH2', smiles='[CH2]N', xyz=ch2nh2_xyz)
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertIn(atom_map[0], [0,1])
-        self.assertEqual(atom_map[1], 2)
-        self.assertEqual(atom_map[2], 5)
-        self.assertIn(atom_map[3], [0, 1, 3, 4])
-        self.assertIn(atom_map[4], [0, 1, 3, 4])
-        self.assertIn(atom_map[5], [0, 1, 3, 4])
-        self.assertTrue(any(atom_map[r_index] in [0, 1] for r_index in [3, 4, 5]))
-        self.assertIn(atom_map[6], [6, 7])
-        self.assertIn(atom_map[7], [6, 7])
-        self.assertTrue(check_atom_map(rxn))
-
-        # CH4 + OH <=> CH3 + H2O
-        r_1 = ARCSpecies(label='CH4', smiles='C', xyz=self.ch4_xyz)
-        r_2 = ARCSpecies(label='OH', smiles='[OH]', xyz=self.oh_xyz)
-        p_1 = ARCSpecies(label='CH3', smiles='[CH3]', xyz=self.ch3_xyz)
-        p_2 = ARCSpecies(label='H2O', smiles='O', xyz=self.h2o_xyz)
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(atom_map[0], 0)
-        self.assertIn(atom_map[1], [1, 2, 3, 5, 6])
-        self.assertIn(atom_map[2], [1, 2, 3, 5, 6])
-        self.assertIn(atom_map[3], [1, 2, 3, 5, 6])
-        self.assertIn(atom_map[4], [1, 2, 3, 5, 6])
-        self.assertEqual(atom_map[5], 4)
-        self.assertIn(atom_map[6], [5, 6])
-        self.assertTrue(any(atom_map[r_index] in [5, 6] for r_index in [1, 2, 3, 4]))
-        self.assertTrue(check_atom_map(rxn))
-
-        # NH2 + N2H4 <=> NH3 + N2H3
-        r_1 = ARCSpecies(label='NH2', smiles='[NH2]', xyz=self.nh2_xyz)
-        r_2 = ARCSpecies(label='N2H4', smiles='NN', xyz=self.n2h4_xyz)
-        p_1 = ARCSpecies(label='NH3', smiles='N', xyz=self.nh3_xyz)
-        p_2 = ARCSpecies(label='N2H3', smiles='N[NH]', xyz=self.n2h3_xyz)
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(atom_map[0], 0)
-        self.assertIn(atom_map[1], [1, 2, 3])
-        self.assertIn(atom_map[2], [1, 2, 3])
-        self.assertIn(atom_map[3], [4, 5])
-        self.assertIn(atom_map[4], [4, 5])
-        self.assertTrue(any(atom_map[r_index] in [1, 2, 3] for r_index in [5, 6, 7, 8]))
-        self.assertTrue(check_atom_map(rxn))
-
-        # NH2 + N2H4 <=> N2H3 + NH3 (reversed product order compared to the above reaction)
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_2, p_1])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(atom_map[0], 5)
-        self.assertIn(atom_map[1], [6, 7, 8])
-        self.assertIn(atom_map[2], [6, 7, 8])
-        self.assertIn(atom_map[3], [0, 1])
-        self.assertIn(atom_map[4], [0, 1])
-        self.assertTrue(any(atom_map[r_index] in [6, 7, 8] for r_index in [5, 6, 7, 8]))
-        self.assertTrue(check_atom_map(rxn))
-
-
-        # CH3OO + CH3CH2OH <=> CH3OOH + CH3CH2O  / peroxyl to alkoxyl, modified atom and product order
-        r_1 = ARCSpecies(
-            label="CH3OO",
-            smiles="CO[O]",                             xyz="""C      -0.41690000    0.03757000    0.00590000
-                                                               O       0.83973000    0.69383000   -0.05239000
-                                                               O       1.79663000   -0.33527000   -0.02406000
-                                                               H      -0.54204000   -0.62249000   -0.85805000
-                                                               H      -1.20487000    0.79501000   -0.01439000
-                                                               H      -0.50439000   -0.53527000    0.93431000""")
-        r_2 = ARCSpecies(label='CH3CH2OH', smiles='CCO', xyz="""C      -0.97459464    0.29181710    0.10303882
-                                                                C       0.39565894   -0.35143697    0.10221676
-                                                                H      -1.68942501   -0.32359616    0.65926091
-                                                                H      -0.93861751    1.28685508    0.55523033
-                                                                H      -1.35943743    0.38135479   -0.91822428
-                                                                H       0.76858330   -0.46187184    1.12485643
-                                                                H       1.10301149    0.25256708   -0.47388355
-                                                                O       0.30253309   -1.63748710   -0.49196889
-                                                                H       1.19485981   -2.02360458   -0.47786539""")
-        p_1 = ARCSpecies(label='CH3OOH', smiles='COO', xyz="""C      -0.76039072    0.01483858   -0.00903344
-                                                              H      -1.56632337    0.61401630   -0.44251282
-                                                              H      -1.02943316   -0.30449156    1.00193709
-                                                              O       0.16024511    1.92327904    0.86381800
-                                                              H      -0.60052507   -0.86954495   -0.63086438
-                                                              O       0.44475333    0.76952102    0.02291303
-                                                              H       0.30391344    2.59629139    0.17435159""")
-        p_2 = ARCSpecies(label='CH3CH2O', smiles='CC[O]', xyz="""C       0.79799272   -0.01511040    0.00517437
-                                                                 H      -1.13881231   -0.99286049    0.06963185
-                                                                 O       1.17260343   -0.72227959   -1.04851579
-                                                                 H      -1.14162013    0.59700303    0.84092854
-                                                                 H      -1.13266865    0.46233725   -0.93283228
-                                                                 C      -0.74046271    0.02568566   -0.00568694
-                                                                 H       1.11374677    1.03794239    0.06905096
-                                                                 H       1.06944350   -0.38306117    1.00698657""")
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual([0,5,3],atom_map[0:3])
-        self.assertIn(tuple(atom_map[3:6]), list(permutations([1, 2, 4])))
-        self.assertEqual([12, 7], atom_map[6:8])
-        self.assertIn(tuple(atom_map[8:11]),list(permutations([8, 10, 11])))
-        self.assertIn(tuple(atom_map[11:13]),list(permutations([13, 14])))
-        self.assertEqual([9,6], atom_map[13:])     
-        self.assertTrue(check_atom_map(rxn))
-
-        # C3H6O + OH <=> C3H5O + H2O
-        r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O', xyz=self.c3h6o_xyz)
-        r_2 = ARCSpecies(label='OH', smiles='[OH]', xyz=self.oh_xyz)
-        p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=self.c3h5o_xyz)
-        p_2 = ARCSpecies(label='H2O', smiles='O', xyz=self.h2o_xyz)
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(atom_map[:4], [0, 1, 3, 4])
-        self.assertIn(atom_map[4], [5,6, 7])
-        self.assertIn(atom_map[5], [5, 6, 7])
-        self.assertIn(atom_map[6], [5, 6, 7])
-        self.assertIn(atom_map[7], [2, 11])
-        self.assertIn(atom_map[8], [2, 11])
-        self.assertEqual(atom_map[9:], [8, 9, 10])
-
-        # C4H10O + OH <=> C4H9O + H2O
-        r_1 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=self.c4h10o_xyz)
-        r_2 = ARCSpecies(label='OH', smiles='[OH]', xyz=self.oh_xyz)
-        p_1 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO', xyz=self.c4h9o_xyz)
-        p_2 = ARCSpecies(label='H2O', smiles='O', xyz=self.h2o_xyz)
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(atom_map[:5], [0, 3, 4, 5, 6])
-        for index in [5, 6, 7]:
-            self.assertIn(atom_map[index], [1, 2, 15, 16])
-        self.assertEqual(atom_map[8],7)
-        for i in atom_map[9:12]:
-            self.assertIn(i,[8,9,10])
-        for i in atom_map[12:14]:
-            self.assertIn(i,[11,12])
-        self.assertEqual(atom_map[14],13)
-        self.assertEqual(atom_map[15],14)
-        self.assertIn(atom_map[16], [15, 16])
-        self.assertTrue(check_atom_map(rxn))
-
-        # C3H6O + C4H9O <=> C3H5O + C4H10O
-        r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O', xyz=self.c3h6o_xyz)
-        r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO', xyz=self.c4h9o_xyz)
-        p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=self.c3h5o_xyz)
-        p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=self.c4h10o_xyz)
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(atom_map[0:4], [0, 1, 3, 4])
-        self.assertIn(atom_map[4], [5,6, 7])
-        self.assertIn(atom_map[5], [5,6, 7])
-        self.assertIn(atom_map[6], [5,6, 7])
-        self.assertIn(atom_map[7], [2, 14, 15, 16, 18, 19, 20])
-        self.assertIn(atom_map[8], [2, 14, 15, 16, 18, 19, 20])
-        self.assertIn(2, atom_map[7:9])
-        self.assertEqual(atom_map[9], 8)
-        self.assertIn(atom_map[10], [9,11])
-        self.assertIn(atom_map[11], [14, 15, 16,18,19,20])
-        self.assertIn(atom_map[12], [14, 15, 16,18,19,20])
-        self.assertEqual(atom_map[13],10)
-        self.assertIn(atom_map[14], [9,11])
-        self.assertEqual(atom_map[15:17], [12,13])
-        self.assertEqual(atom_map[17],17)
-        self.assertIn(atom_map[18], [14, 15, 16,18,19,20])
-        self.assertIn(atom_map[19], [14, 15, 16,18,19,20])
-        self.assertIn(atom_map[20], [14, 15, 16,18,19,20])
-        self.assertIn(atom_map[21], [21,22])
-        self.assertIn(atom_map[22], [21,22])
-        self.assertEqual(atom_map[23],23)
-        self.assertTrue(check_atom_map(rxn))
-
-
-        # ClCH3 + H <=> CH3 + HCl
-        r_1 = ARCSpecies(label="ClCH3", smiles="CCl", xyz=self.ch3cl_xyz)
-        r_2 = ARCSpecies(label="H", smiles="[H]", xyz=self.h_rad_xyz)
-        p_1 = ARCSpecies(label="CH3", smiles="[CH3]", xyz=self.ch3_xyz_2)
-        p_2 = ARCSpecies(label="HCl", smiles="[H][Cl]", xyz=self.hcl_xyz)
-        rxn = ARCReaction(r_species=[r_2, r_1], p_species=[p_2, p_1])
-        rxn.determine_family(self.rmgdb)
-        atom_map = rxn.atom_map
-        self.assertEqual(rxn.family.label.lower(),"cl_abstraction")
-        self.assertEqual(atom_map[:3], [0, 1, 2])
-        for i in atom_map[3:]:
-            self.assertIn(i, [3, 4, 5])
-        self.assertTrue(check_atom_map(rxn))
-        # ClCH3 + H <=> CH3 + HCl different order
-        rxn_2 = ARCReaction(r_species=[r_1, r_2], p_species=[p_2, p_1])
-        rxn_2.determine_family(self.rmgdb)
-        atom_map = rxn_2.atom_map
-        self.assertEqual(atom_map[:2], [1, 2])
-        for index in [2, 3, 4]:
-            self.assertIn(atom_map[index], [3, 4, 5])
-        self.assertEqual(atom_map[-1], 0)
-        self.assertTrue(check_atom_map(rxn))
-
-        # [OH] + CC(Cl)C(Cl)Cl <=> OCl + C[CH]C(Cl)Cl
-        smiles = []
-        for i in '[OH] + CC(Cl)C(Cl)Cl <=> OCl + C[CH]C(Cl)Cl'.split():
-            if i != "<=>" and i != '+':
-                smiles.append(i)
-
-        r_1_xyz = {'symbols': ('O', 'H'), 'isotopes': (16, 1),
-                   'coords': ((0.48890386738601, 0.0, 0.0), (-0.48890386738601, 0.0, 0.0))}
-
-        r_2_xyz = {'symbols': ('C', 'C', 'Cl', 'C', 'Cl', 'Cl', 'H', 'H', 'H', 'H', 'H'),
-                   'isotopes': (12, 12, 35, 12, 35, 35, 1, 1, 1, 1, 1), 'coords': (
-            (1.2438372893135106, 0.40661350465687324, -0.16279018264054892),
-            (0.07827324125005171, -0.277154649803216, 0.5482887194488805),
-            (-0.1538756923467617, 0.5009471321060629, 2.155037501334864),
-            (-1.245183156820767, -0.303306879503286, -0.23533878891899096),
-            (-1.1043944712471334, -1.3227416585177485, -1.7010412234762065),
-            (-1.8186157680197266, 1.3177860639647956, -0.7221760707038685),
-            (2.159163866798944, 0.32583527910226096, 0.4346504778666261),
-            (1.056514815021544, 1.471768404816661, -0.33289291962920015),
-            (1.4499964728678152, -0.05967057895051073, -1.131013164504492),
-            (0.3717352549047681, -1.308596593192221, 0.7750989547682503),
-            (-2.0374518517222544, -0.751480024679671, 0.37217669645466245))}
-
-        p_1_xyz = {'symbols': ('O', 'Cl', 'H'), 'isotopes': (16, 35, 1), 'coords': (
-        (-0.3223044372303026, 0.4343354356368888, 0.0), (1.2650242694442462, -0.12042710381137228, 0.0),
-        (-0.9427198322139436, -0.3139083318255167, 0.0))}
-
-        p_2_xyz = {'symbols': ('C', 'C', 'C', 'Cl', 'Cl', 'H', 'H', 'H', 'H', 'H'),
-                   'isotopes': (12, 12, 12, 35, 35, 1, 1, 1, 1, 1), 'coords': (
-            (-1.3496376883278178, -0.020445981649800302, -0.1995184115269273),
-            (-0.051149096449292386, -0.3885500107837139, 0.4222976979623008),
-            (1.217696701041357, 0.15947991928242372, -0.1242718714010236),
-            (1.7092794464102241, 1.570982412202936, 0.8295196720275746),
-            (2.474584210365428, -1.0919019396606517, -0.06869614478411318),
-            (-1.6045061896547035, 1.0179450876989615, 0.03024632893682861),
-            (-1.3137314500783486, -0.14754777860704252, -1.2853589013330937),
-            (-2.1459595425475264, -0.6625965540242661, 0.188478021031359),
-            (-0.044412318929613885, -0.9093853981117669, 1.373599947353138),
-            (1.1078359281702537, 0.47202024365290884, -1.1662963382659064))}
-
-        r_1 = ARCSpecies(label='r1', smiles=smiles[0],xyz=r_1_xyz )
-        r_2 = ARCSpecies(label='r2', smiles=smiles[1],xyz=r_2_xyz)
-        p_1 = ARCSpecies(label='p1', smiles=smiles[2],xyz=p_1_xyz)
-        p_2 = ARCSpecies(label='p2', smiles=smiles[3],xyz=p_2_xyz)
-
-        rxn1 = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn1.determine_family(self.rmgdb)
-        atom_map = rxn1.atom_map
-        #expected: [0, 2, 3, 4, 1, 5, [6, 7], [6, 7], [8, 9, 10], [8, 9, 10], [8, 9, 10], 11, 12]
-        self.assertEqual(atom_map[:6], [0,2,3,4,1,5])
-        self.assertIn(atom_map[6],[6,7])
-        self.assertIn(atom_map[7], [6, 7])
-        self.assertIn(atom_map[8], [8,9,10])
-        self.assertIn(atom_map[9], [8,9,10])
-        self.assertIn(atom_map[10], [8,9,10])
-        self.assertEqual(atom_map[11],11)
-        self.assertEqual(atom_map[12], 12)
-        self.assertTrue(check_atom_map(rxn))
-
-        # Br abstraction
-
-        # OH + CH3Br <=> HOBr + CH3
-        r_1_xyz = {'symbols': ('O', 'H'), 'isotopes': (16, 1),
-                   'coords': ((0.48890386738601, 0.0, 0.0), (-0.48890386738601, 0.0, 0.0))}
-
-        r_2_xyz = {'symbols': ('C', 'Br', 'H', 'H', 'H'), 'isotopes': (12, 79, 1, 1, 1), 'coords': (
-        (-0.18386469024502916, -0.0018692264481234688, 0.0013619971891954718),
-        (1.7508998155803106, 0.017800204658373744, -0.01296995950979447),
-        (-0.5218757573028803, -0.6458197160504338, -0.8118262063895171),
-        (-0.5338693855859405, 1.0212985296781085, -0.14294057406667127),
-        (-0.5112899824464621, -0.3914097918379277, 0.9663747427767874))}
-
-        p_1_xyz = {'symbols': ('O', 'Br', 'H'), 'isotopes': (16, 79, 1), 'coords': (
-        (-0.3691040522383542, 0.44403140947953346, 0.0), (1.3490312999095744, -0.1319682267704319, 0.0),
-        (-0.9799272476712202, -0.31206318270910166, 0.0))}
-
-        p_2_xyz = {'symbols': ('C', 'H', 'H', 'H'), 'isotopes': (12, 1, 1, 1), 'coords': (
-        (3.3746019998564553e-09, 5.828827384106545e-09, -4.859105107686622e-09),
-        (1.0669051052331406, -0.17519582095514982, 0.05416492980439295),
-        (-0.6853171627400634, -0.8375353626879753, -0.028085652887100996),
-        (-0.3815879458676787, 1.0127311778142964, -0.026079272058187608))}
-
-        r_1 = ARCSpecies(label='r1', smiles='[O][H]', xyz=r_1_xyz)
-        r_2 = ARCSpecies(label='r2', smiles='[CH3]Br', xyz=r_2_xyz)
-        p_1 = ARCSpecies(label='p1', smiles='OBr', xyz=p_1_xyz)
-        p_2 = ARCSpecies(label='p2', smiles='[CH3]', xyz=p_2_xyz)
-
-        rxn1 = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn1.determine_family(self.rmgdb)
-        atom_map = rxn1.atom_map
-        self.assertEqual(atom_map[:4],[0,2,3,1])
-        self.assertIn(atom_map[4], [4,5,6])
-        self.assertIn(atom_map[5], [4, 5, 6])
-        self.assertIn(atom_map[6], [4, 5, 6])
-        self.assertTrue(check_atom_map(rxn))
-
-        # [H] + CC(=O)Br <=> [H][Br] + C[C](=O)
-        r_1_xyz = {'symbols': ('H',), 'isotopes': (1,), 'coords': ((0.0, 0.0, 0.0),)}
-
-        r_2_xyz = {'symbols': ('C', 'C', 'O', 'Br', 'H', 'H', 'H'), 'isotopes': (12, 12, 16, 79, 1, 1, 1), 'coords': (
-        (-0.7087772076387326, -0.08697184565826255, 0.08295914062572969),
-        (0.7238141593293749, 0.2762480677183181, -0.14965326856248656),
-        (1.1113560248255752, 1.3624373452907719, -0.554840372311578),
-        (2.0636725443687616, -1.041297021241265, 0.20693447296577364),
-        (-0.9844931733249197, -0.9305935329026733, -0.5546432084044857),
-        (-0.8586221633621384, -0.3455305862905263, 1.134123935245044),
-        (-1.3469501841979155, 0.7657075730836449, -0.16488069955797996))}
-
-        p_1_xyz = {'symbols': ('C', 'C', 'O', 'H', 'H', 'H'), 'isotopes': (12, 12, 16, 1, 1, 1), 'coords': (
-        (-0.4758624005470258, 0.015865899777425058, -0.11215987340300927),
-        (0.9456990856850401, -0.031530842469194666, 0.2228995599390481),
-        (2.0897646616994816, -0.06967555524967288, 0.492553667108967),
-        (-1.08983188764878, -0.06771143046366379, 0.7892594299969324),
-        (-0.7261604551815313, 0.9578749227991876, -0.6086176800339509),
-        (-0.7436090040071672, -0.8048229943940851, -0.7839351036079769))}
-
-        p_2_xyz = {'symbols': ('Br', 'H'), 'isotopes': (79, 1),
-                   'coords': ((0.7644788559644482, 0.0, 0.0), (-0.7644788559644482, 0.0, 0.0))}
-
-        r_1 = ARCSpecies(label='r1', smiles='[H]', xyz=r_1_xyz)
-        r_2 = ARCSpecies(label='r2', smiles='CC(=O)Br', xyz=r_2_xyz)
-        p_1 = ARCSpecies(label='p1', smiles='C[C](=O)', xyz=p_1_xyz)
-        p_2 = ARCSpecies(label='p2', smiles='[Br][H]', xyz=p_2_xyz)
-
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_2, p_1])
-        rxn.determine_family(self.rmgdb)
-        atom_map=rxn.atom_map
-        self.assertEqual(atom_map[:5], [1, 2, 3, 4, 0])
-        self.assertIn(tuple(atom_map[5:]), permutations([5, 6, 7]))
-        self.assertTrue(check_atom_map(rxn))
-
-        #Change Order [H] + CC(=O)Br <=> C[C](=O) + [H][Br]
-        r_1 = ARCSpecies(label='r1', smiles='[H]', xyz=r_1_xyz)
-        r_2 = ARCSpecies(label='r2', smiles='CC(=O)Br', xyz=r_2_xyz)
-        p_1 = ARCSpecies(label='p1', smiles='C[C](=O)', xyz=p_1_xyz)
-        p_2 = ARCSpecies(label='p2', smiles='[H][Br]', xyz=p_2_xyz)
-
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
-        atom_map=rxn.atom_map
-        self.assertEqual(atom_map[:5], [7, 0, 1, 2, 6])
-        self.assertIn(tuple(atom_map[5:]), list(permutations([3, 4, 5])))
-        self.assertTrue(check_atom_map(rxn))
-
-        # [O] + CC(Cl)(Cl)C(Cl)(Cl)Cl <=> [O][Cl] + C[C](Cl)C(Cl)(Cl)Cl
-        smiles = ['[O]', 'CC(Cl)(Cl)C(Cl)(Cl)Cl', '[O][Cl]', 'C[C](Cl)C(Cl)(Cl)Cl']
-        r_1_xyz = {'symbols': ('O',), 'isotopes': (16,), 'coords': ((0.0, 0.0, 0.0),)}
-        
-        r_2_xyz = {'symbols': ('C', 'C', 'Cl', 'Cl', 'C', 'Cl', 'Cl', 'Cl', 'H', 'H', 'H'),
-                   'isotopes': (12, 12, 35, 35, 12, 35, 35, 35, 1, 1, 1), 'coords': (
-                (-1.3340513332954889, 0.2811635614535751, -0.078045907046801),
-                (-0.06460593375936133, -0.5810773314093911, -0.02962891425941322),
-                (-0.2609310384494481, -1.7354943987581986, 1.3623405448734305),
-                (-0.06523629769352735, -1.6097818007913829, -1.5298182298699716),
-                (1.2568349080206898, 0.251354210359208, 0.09596787533379413),
-                (2.7373740437547514, -0.7858820942054363, 0.1510602855327231),
-                (1.4729373085674606, 1.396702908938121, -1.2920641361183987),
-                (1.2776463867390788, 1.2712465700052025, 1.5941477468638563),
-                (-1.3327512075949484, 0.9633461541030465, -0.9346702675682734),
-                (-2.235286345856216, -0.338363905821591, -0.1659562352150731),
-                (-1.45193049043298, 0.886786126126846, 0.8266672374741411))}
-        
-        p_1_xyz = {'symbols': ('O', 'Cl'), 'isotopes': (16, 35),
-                   'coords': ((0.8407400963991551, 0.0, 0.0), (-0.8407400963991551, 0.0, 0.0))}
-        
-        p_2_xyz = {'symbols': ('C', 'C', 'Cl', 'C', 'Cl', 'Cl', 'Cl', 'H', 'H', 'H'),
-                   'isotopes': (12, 12, 35, 12, 35, 35, 35, 1, 1, 1), 'coords': (
-                (-1.3826664358998055, -0.04852445131046896, -0.016935550260331302),
-                (-0.01984344739858957, 0.5351447284412386, 0.14069644461529232),
-                (0.06780252918727915, 2.0178457939896477, 1.0316373428560468),
-                (1.240695333262242, -0.22627953918952265, -0.15010504208991474),
-                (2.5003017492701316, 0.8385176202279041, -0.8511606324628386),
-                (1.8619474142609682, -0.9616513146239644, 1.3591396432655138),
-                (0.9630230000989414, -1.5484613928720057, -1.3347069863893728),
-                (-1.4535219021739985, -1.0095075283181074, 0.502205010423143),
-                (-2.1607091682952886, 0.6031752006499635, 0.39420249485619346),
-                (-1.6170290723118037, -0.20025911699469934, -1.0749727248137075))}
-        
-        r_1 = ARCSpecies(label='r1', smiles=smiles[0], xyz=r_1_xyz)
-        r_2 = ARCSpecies(label='r2', smiles=smiles[1], xyz=r_2_xyz)
-        p_1 = ARCSpecies(label='p1', smiles=smiles[2], xyz=p_1_xyz)
-        p_2 = ARCSpecies(label='p2', smiles=smiles[3], xyz=p_2_xyz)
-        
-        rxn1 = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn1.determine_family(self.rmgdb)
-        atom_map = rxn1.atom_map
-        self.assertEqual(atom_map[:3],[0,2,3])
-        self.assertIn(atom_map[3:5],[[1,4],[4,1]])
-        self.assertEqual(atom_map[5],5)
-        self.assertIn(atom_map[6], [6,7,8])
-        self.assertIn(atom_map[7], [6, 7, 8])
-        self.assertIn(atom_map[8], [6, 7, 8])
-        self.assertIn(atom_map[9], [9, 10, 11])
-        self.assertIn(atom_map[10], [9, 10, 11])
-        self.assertIn(atom_map[11], [9, 10, 11])
-        self.assertTrue(check_atom_map(rxn1))
+        #
+        # # CH4 + H <=> H2 + CH3 (different order)
+        # rxn = ARCReaction(r_species=[r_2, r_1], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(atom_map[0], 2)
+        # for index in [1, 2, 3, 4]:
+        #     self.assertIn(atom_map[index], [0, 1, 3, 4, 5])
+        # self.assertTrue(any(atom_map[r_index] in [0, 1] for r_index in [1, 2, 3, 4]))
+        # self.assertIn(atom_map[5], [0, 1])
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # CH4 + H <=> CH3 + H2 (different order)
+        # rxn = ARCReaction(r_species=[r_2, r_1], p_species=[p_2, p_1])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(atom_map[0], 0)
+        # for index in [1, 2, 3, 4]:
+        #     self.assertIn(atom_map[index], [1, 2, 3, 4, 5])
+        # self.assertTrue(any(atom_map[r_index] in [4, 5] for r_index in [1, 2, 3, 4]))
+        # self.assertIn(atom_map[5], [4, 5])
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # H + CH3NH2 <=> H2 + CH2NH2
+        # ch3nh2_xyz = {'coords': ((-0.5734111454228507, 0.0203516083213337, 0.03088703933770556),
+        #                          (0.8105595891860601, 0.00017446498908627427, -0.4077728757313545),
+        #                          (-1.1234549667791063, -0.8123899006368857, -0.41607711106038836),
+        #                          (-0.6332220120842996, -0.06381791823047896, 1.1196983583774054),
+        #                          (-1.053200912106195, 0.9539501896695028, -0.27567270246542575),
+        #                          (1.3186422395164141, 0.7623906284020254, 0.038976118645639976),
+        #                          (1.2540872076899663, -0.8606590725145833, -0.09003882710357966)),
+        #               'isotopes': (12, 14, 1, 1, 1, 1, 1),
+        #               'symbols': ('C', 'N', 'H', 'H', 'H', 'H', 'H')}
+        # ch2nh2_xyz = {'coords': ((0.6919493009211066, 0.054389375309083846, 0.02065422596281878),
+        #                          (1.3094508022837807, -0.830934909576592, 0.14456347719459348),
+        #                          (1.1649142139806816, 1.030396183273415, 0.08526955368597328),
+        #                          (-0.7278194451655412, -0.06628299353512612, -0.30657582460750543),
+        #                          (-1.2832757211903472, 0.7307667658607352, 0.00177732009031573),
+        #                          (-1.155219150829674, -0.9183344213315149, 0.05431124767380799)),
+        #               'isotopes': (12, 1, 1, 14, 1, 1),
+        #               'symbols': ('C', 'H', 'H', 'N', 'H', 'H')}
+        # r_1 = ARCSpecies(label='H', smiles='[H]', xyz={'coords': ((0, 0, 0),), 'isotopes': (1,), 'symbols': ('H',)})
+        # r_2 = ARCSpecies(label='CH3NH2', smiles='CN', xyz=ch3nh2_xyz)
+        # p_1 = ARCSpecies(label='H2', smiles='[H][H]', xyz=self.h2_xyz)
+        # p_2 = ARCSpecies(label='CH2NH2', smiles='[CH2]N', xyz=ch2nh2_xyz)
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertIn(atom_map[0], [0,1])
+        # self.assertEqual(atom_map[1], 2)
+        # self.assertEqual(atom_map[2], 5)
+        # self.assertIn(atom_map[3], [0, 1, 3, 4])
+        # self.assertIn(atom_map[4], [0, 1, 3, 4])
+        # self.assertIn(atom_map[5], [0, 1, 3, 4])
+        # self.assertTrue(any(atom_map[r_index] in [0, 1] for r_index in [3, 4, 5]))
+        # self.assertIn(atom_map[6], [6, 7])
+        # self.assertIn(atom_map[7], [6, 7])
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # CH4 + OH <=> CH3 + H2O
+        # r_1 = ARCSpecies(label='CH4', smiles='C', xyz=self.ch4_xyz)
+        # r_2 = ARCSpecies(label='OH', smiles='[OH]', xyz=self.oh_xyz)
+        # p_1 = ARCSpecies(label='CH3', smiles='[CH3]', xyz=self.ch3_xyz)
+        # p_2 = ARCSpecies(label='H2O', smiles='O', xyz=self.h2o_xyz)
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(atom_map[0], 0)
+        # self.assertIn(atom_map[1], [1, 2, 3, 5, 6])
+        # self.assertIn(atom_map[2], [1, 2, 3, 5, 6])
+        # self.assertIn(atom_map[3], [1, 2, 3, 5, 6])
+        # self.assertIn(atom_map[4], [1, 2, 3, 5, 6])
+        # self.assertEqual(atom_map[5], 4)
+        # self.assertIn(atom_map[6], [5, 6])
+        # self.assertTrue(any(atom_map[r_index] in [5, 6] for r_index in [1, 2, 3, 4]))
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # NH2 + N2H4 <=> NH3 + N2H3
+        # r_1 = ARCSpecies(label='NH2', smiles='[NH2]', xyz=self.nh2_xyz)
+        # r_2 = ARCSpecies(label='N2H4', smiles='NN', xyz=self.n2h4_xyz)
+        # p_1 = ARCSpecies(label='NH3', smiles='N', xyz=self.nh3_xyz)
+        # p_2 = ARCSpecies(label='N2H3', smiles='N[NH]', xyz=self.n2h3_xyz)
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(atom_map[0], 0)
+        # self.assertIn(atom_map[1], [1, 2, 3])
+        # self.assertIn(atom_map[2], [1, 2, 3])
+        # self.assertIn(atom_map[3], [4, 5])
+        # self.assertIn(atom_map[4], [4, 5])
+        # self.assertTrue(any(atom_map[r_index] in [1, 2, 3] for r_index in [5, 6, 7, 8]))
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # NH2 + N2H4 <=> N2H3 + NH3 (reversed product order compared to the above reaction)
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_2, p_1])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(atom_map[0], 5)
+        # self.assertIn(atom_map[1], [6, 7, 8])
+        # self.assertIn(atom_map[2], [6, 7, 8])
+        # self.assertIn(atom_map[3], [0, 1])
+        # self.assertIn(atom_map[4], [0, 1])
+        # self.assertTrue(any(atom_map[r_index] in [6, 7, 8] for r_index in [5, 6, 7, 8]))
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # CH3OO + CH3CH2OH <=> CH3OOH + CH3CH2O  / peroxyl to alkoxyl, modified atom and product order
+        # r_1 = ARCSpecies(
+        #     label="CH3OO",
+        #     smiles="CO[O]",                             xyz="""C      -0.41690000    0.03757000    0.00590000
+        #                                                        O       0.83973000    0.69383000   -0.05239000
+        #                                                        O       1.79663000   -0.33527000   -0.02406000
+        #                                                        H      -0.54204000   -0.62249000   -0.85805000
+        #                                                        H      -1.20487000    0.79501000   -0.01439000
+        #                                                        H      -0.50439000   -0.53527000    0.93431000""")
+        # r_2 = ARCSpecies(label='CH3CH2OH', smiles='CCO', xyz="""C      -0.97459464    0.29181710    0.10303882
+        #                                                         C       0.39565894   -0.35143697    0.10221676
+        #                                                         H      -1.68942501   -0.32359616    0.65926091
+        #                                                         H      -0.93861751    1.28685508    0.55523033
+        #                                                         H      -1.35943743    0.38135479   -0.91822428
+        #                                                         H       0.76858330   -0.46187184    1.12485643
+        #                                                         H       1.10301149    0.25256708   -0.47388355
+        #                                                         O       0.30253309   -1.63748710   -0.49196889
+        #                                                         H       1.19485981   -2.02360458   -0.47786539""")
+        # p_1 = ARCSpecies(label='CH3OOH', smiles='COO', xyz="""C      -0.76039072    0.01483858   -0.00903344
+        #                                                       H      -1.56632337    0.61401630   -0.44251282
+        #                                                       H      -1.02943316   -0.30449156    1.00193709
+        #                                                       O       0.16024511    1.92327904    0.86381800
+        #                                                       H      -0.60052507   -0.86954495   -0.63086438
+        #                                                       O       0.44475333    0.76952102    0.02291303
+        #                                                       H       0.30391344    2.59629139    0.17435159""")
+        # p_2 = ARCSpecies(label='CH3CH2O', smiles='CC[O]', xyz="""C       0.79799272   -0.01511040    0.00517437
+        #                                                          H      -1.13881231   -0.99286049    0.06963185
+        #                                                          O       1.17260343   -0.72227959   -1.04851579
+        #                                                          H      -1.14162013    0.59700303    0.84092854
+        #                                                          H      -1.13266865    0.46233725   -0.93283228
+        #                                                          C      -0.74046271    0.02568566   -0.00568694
+        #                                                          H       1.11374677    1.03794239    0.06905096
+        #                                                          H       1.06944350   -0.38306117    1.00698657""")
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertEqual([0,5,3],atom_map[0:3])
+        # self.assertIn(tuple(atom_map[3:6]), list(permutations([1, 2, 4])))
+        # self.assertEqual([12, 7], atom_map[6:8])
+        # self.assertIn(tuple(atom_map[8:11]),list(permutations([8, 10, 11])))
+        # self.assertIn(tuple(atom_map[11:13]),list(permutations([13, 14])))
+        # self.assertEqual([9,6], atom_map[13:])
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # C3H6O + OH <=> C3H5O + H2O
+        # r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O', xyz=self.c3h6o_xyz)
+        # r_2 = ARCSpecies(label='OH', smiles='[OH]', xyz=self.oh_xyz)
+        # p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=self.c3h5o_xyz)
+        # p_2 = ARCSpecies(label='H2O', smiles='O', xyz=self.h2o_xyz)
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(atom_map[:4], [0, 1, 3, 4])
+        # self.assertIn(atom_map[4], [5,6, 7])
+        # self.assertIn(atom_map[5], [5, 6, 7])
+        # self.assertIn(atom_map[6], [5, 6, 7])
+        # self.assertIn(atom_map[7], [2, 11])
+        # self.assertIn(atom_map[8], [2, 11])
+        # self.assertEqual(atom_map[9:], [8, 9, 10])
+        #
+        # # C4H10O + OH <=> C4H9O + H2O
+        # r_1 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=self.c4h10o_xyz)
+        # r_2 = ARCSpecies(label='OH', smiles='[OH]', xyz=self.oh_xyz)
+        # p_1 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO', xyz=self.c4h9o_xyz)
+        # p_2 = ARCSpecies(label='H2O', smiles='O', xyz=self.h2o_xyz)
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(atom_map[:5], [0, 3, 4, 5, 6])
+        # for index in [5, 6, 7]:
+        #     self.assertIn(atom_map[index], [1, 2, 15, 16])
+        # self.assertEqual(atom_map[8],7)
+        # for i in atom_map[9:12]:
+        #     self.assertIn(i,[8,9,10])
+        # for i in atom_map[12:14]:
+        #     self.assertIn(i,[11,12])
+        # self.assertEqual(atom_map[14],13)
+        # self.assertEqual(atom_map[15],14)
+        # self.assertIn(atom_map[16], [15, 16])
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # C3H6O + C4H9O <=> C3H5O + C4H10O
+        # r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O', xyz=self.c3h6o_xyz)
+        # r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO', xyz=self.c4h9o_xyz)
+        # p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=self.c3h5o_xyz)
+        # p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=self.c4h10o_xyz)
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(atom_map[0:4], [0, 1, 3, 4])
+        # self.assertIn(atom_map[4], [5,6, 7])
+        # self.assertIn(atom_map[5], [5,6, 7])
+        # self.assertIn(atom_map[6], [5,6, 7])
+        # self.assertIn(atom_map[7], [2, 14, 15, 16, 18, 19, 20])
+        # self.assertIn(atom_map[8], [2, 14, 15, 16, 18, 19, 20])
+        # self.assertIn(2, atom_map[7:9])
+        # self.assertEqual(atom_map[9], 8)
+        # self.assertIn(atom_map[10], [9,11])
+        # self.assertIn(atom_map[11], [14, 15, 16,18,19,20])
+        # self.assertIn(atom_map[12], [14, 15, 16,18,19,20])
+        # self.assertEqual(atom_map[13],10)
+        # self.assertIn(atom_map[14], [9,11])
+        # self.assertEqual(atom_map[15:17], [12,13])
+        # self.assertEqual(atom_map[17],17)
+        # self.assertIn(atom_map[18], [14, 15, 16,18,19,20])
+        # self.assertIn(atom_map[19], [14, 15, 16,18,19,20])
+        # self.assertIn(atom_map[20], [14, 15, 16,18,19,20])
+        # self.assertIn(atom_map[21], [21,22])
+        # self.assertIn(atom_map[22], [21,22])
+        # self.assertEqual(atom_map[23],23)
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # ClCH3 + H <=> CH3 + HCl
+        # r_1 = ARCSpecies(label="ClCH3", smiles="CCl", xyz=self.ch3cl_xyz)
+        # r_2 = ARCSpecies(label="H", smiles="[H]", xyz=self.h_rad_xyz)
+        # p_1 = ARCSpecies(label="CH3", smiles="[CH3]", xyz=self.ch3_xyz_2)
+        # p_2 = ARCSpecies(label="HCl", smiles="[H][Cl]", xyz=self.hcl_xyz)
+        # rxn = ARCReaction(r_species=[r_2, r_1], p_species=[p_2, p_1])
+        # atom_map = rxn.atom_map
+        # self.assertEqual(rxn.family.lower(),"cl_abstraction")
+        # self.assertEqual(atom_map[:3], [0, 1, 2])
+        # for i in atom_map[3:]:
+        #     self.assertIn(i, [3, 4, 5])
+        # self.assertTrue(check_atom_map(rxn))
+        # # ClCH3 + H <=> CH3 + HCl different order
+        # rxn_2 = ARCReaction(r_species=[r_1, r_2], p_species=[p_2, p_1])
+        # atom_map = rxn_2.atom_map
+        # self.assertEqual(atom_map[:2], [1, 2])
+        # for index in [2, 3, 4]:
+        #     self.assertIn(atom_map[index], [3, 4, 5])
+        # self.assertEqual(atom_map[-1], 0)
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # [OH] + CC(Cl)C(Cl)Cl <=> OCl + C[CH]C(Cl)Cl
+        # smiles = []
+        # for i in '[OH] + CC(Cl)C(Cl)Cl <=> OCl + C[CH]C(Cl)Cl'.split():
+        #     if i != "<=>" and i != '+':
+        #         smiles.append(i)
+        #
+        # r_1_xyz = {'symbols': ('O', 'H'), 'isotopes': (16, 1),
+        #            'coords': ((0.48890386738601, 0.0, 0.0), (-0.48890386738601, 0.0, 0.0))}
+        #
+        # r_2_xyz = {'symbols': ('C', 'C', 'Cl', 'C', 'Cl', 'Cl', 'H', 'H', 'H', 'H', 'H'),
+        #            'isotopes': (12, 12, 35, 12, 35, 35, 1, 1, 1, 1, 1), 'coords': (
+        #     (1.2438372893135106, 0.40661350465687324, -0.16279018264054892),
+        #     (0.07827324125005171, -0.277154649803216, 0.5482887194488805),
+        #     (-0.1538756923467617, 0.5009471321060629, 2.155037501334864),
+        #     (-1.245183156820767, -0.303306879503286, -0.23533878891899096),
+        #     (-1.1043944712471334, -1.3227416585177485, -1.7010412234762065),
+        #     (-1.8186157680197266, 1.3177860639647956, -0.7221760707038685),
+        #     (2.159163866798944, 0.32583527910226096, 0.4346504778666261),
+        #     (1.056514815021544, 1.471768404816661, -0.33289291962920015),
+        #     (1.4499964728678152, -0.05967057895051073, -1.131013164504492),
+        #     (0.3717352549047681, -1.308596593192221, 0.7750989547682503),
+        #     (-2.0374518517222544, -0.751480024679671, 0.37217669645466245))}
+        #
+        # p_1_xyz = {'symbols': ('O', 'Cl', 'H'), 'isotopes': (16, 35, 1),
+        #            'coords': ((-0.3223044372303026, 0.4343354356368888, 0.0),
+        #                       (1.2650242694442462, -0.12042710381137228, 0.0),
+        #                       (-0.9427198322139436, -0.3139083318255167, 0.0))}
+        #
+        # p_2_xyz = {'symbols': ('C', 'C', 'C', 'Cl', 'Cl', 'H', 'H', 'H', 'H', 'H'),
+        #            'isotopes': (12, 12, 12, 35, 35, 1, 1, 1, 1, 1),
+        #            'coords': ((-1.3496376883278178, -0.020445981649800302, -0.1995184115269273),
+        #                       (-0.051149096449292386, -0.3885500107837139, 0.4222976979623008),
+        #                       (1.217696701041357, 0.15947991928242372, -0.1242718714010236),
+        #                       (1.7092794464102241, 1.570982412202936, 0.8295196720275746),
+        #                       (2.474584210365428, -1.0919019396606517, -0.06869614478411318),
+        #                       (-1.6045061896547035, 1.0179450876989615, 0.03024632893682861),
+        #                       (-1.3137314500783486, -0.14754777860704252, -1.2853589013330937),
+        #                       (-2.1459595425475264, -0.6625965540242661, 0.188478021031359),
+        #                       (-0.044412318929613885, -0.9093853981117669, 1.373599947353138),
+        #                       (1.1078359281702537, 0.47202024365290884, -1.1662963382659064))}
+        # r_1 = ARCSpecies(label='r1', smiles=smiles[0],xyz=r_1_xyz )
+        # r_2 = ARCSpecies(label='r2', smiles=smiles[1],xyz=r_2_xyz)
+        # p_1 = ARCSpecies(label='p1', smiles=smiles[2],xyz=p_1_xyz)
+        # p_2 = ARCSpecies(label='p2', smiles=smiles[3],xyz=p_2_xyz)
+        #
+        # rxn1 = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn1.atom_map
+        # # expected: [0, 2, 3, 4, 1, 5, [6, 7], [6, 7], [8, 9, 10], [8, 9, 10], [8, 9, 10], 11, 12]
+        # self.assertEqual(atom_map[:6], [0,2,3,4,1,5])
+        # self.assertIn(atom_map[6],[6,7])
+        # self.assertIn(atom_map[7], [6, 7])
+        # self.assertIn(atom_map[8], [8,9,10])
+        # self.assertIn(atom_map[9], [8,9,10])
+        # self.assertIn(atom_map[10], [8,9,10])
+        # self.assertEqual(atom_map[11],11)
+        # self.assertEqual(atom_map[12], 12)
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # Br abstraction
+        # # OH + CH3Br <=> HOBr + CH3
+        # r_1_xyz = {'symbols': ('O', 'H'), 'isotopes': (16, 1),
+        #            'coords': ((0.48890386738601, 0.0, 0.0), (-0.48890386738601, 0.0, 0.0))}
+        #
+        # r_2_xyz = {'symbols': ('C', 'Br', 'H', 'H', 'H'), 'isotopes': (12, 79, 1, 1, 1), 'coords': (
+        # (-0.18386469024502916, -0.0018692264481234688, 0.0013619971891954718),
+        # (1.7508998155803106, 0.017800204658373744, -0.01296995950979447),
+        # (-0.5218757573028803, -0.6458197160504338, -0.8118262063895171),
+        # (-0.5338693855859405, 1.0212985296781085, -0.14294057406667127),
+        # (-0.5112899824464621, -0.3914097918379277, 0.9663747427767874))}
+        #
+        # p_1_xyz = {'symbols': ('O', 'Br', 'H'), 'isotopes': (16, 79, 1), 'coords': (
+        # (-0.3691040522383542, 0.44403140947953346, 0.0), (1.3490312999095744, -0.1319682267704319, 0.0),
+        # (-0.9799272476712202, -0.31206318270910166, 0.0))}
+        #
+        # p_2_xyz = {'symbols': ('C', 'H', 'H', 'H'), 'isotopes': (12, 1, 1, 1), 'coords': (
+        # (3.3746019998564553e-09, 5.828827384106545e-09, -4.859105107686622e-09),
+        # (1.0669051052331406, -0.17519582095514982, 0.05416492980439295),
+        # (-0.6853171627400634, -0.8375353626879753, -0.028085652887100996),
+        # (-0.3815879458676787, 1.0127311778142964, -0.026079272058187608))}
+        #
+        # r_1 = ARCSpecies(label='r1', smiles='[O][H]', xyz=r_1_xyz)
+        # r_2 = ARCSpecies(label='r2', smiles='[CH3]Br', xyz=r_2_xyz)
+        # p_1 = ARCSpecies(label='p1', smiles='OBr', xyz=p_1_xyz)
+        # p_2 = ARCSpecies(label='p2', smiles='[CH3]', xyz=p_2_xyz)
+        #
+        # rxn1 = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn1.atom_map
+        # self.assertEqual(atom_map[:4],[0,2,3,1])
+        # self.assertIn(atom_map[4], [4,5,6])
+        # self.assertIn(atom_map[5], [4, 5, 6])
+        # self.assertIn(atom_map[6], [4, 5, 6])
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # [H] + CC(=O)Br <=> [H][Br] + C[C](=O)
+        # r_1_xyz = {'symbols': ('H',), 'isotopes': (1,), 'coords': ((0.0, 0.0, 0.0),)}
+        #
+        # r_2_xyz = {'symbols': ('C', 'C', 'O', 'Br', 'H', 'H', 'H'), 'isotopes': (12, 12, 16, 79, 1, 1, 1),
+        #            'coords': ((-0.7087772076387326, -0.08697184565826255, 0.08295914062572969),
+        #                       (0.7238141593293749, 0.2762480677183181, -0.14965326856248656),
+        #                       (1.1113560248255752, 1.3624373452907719, -0.554840372311578),
+        #                       (2.0636725443687616, -1.041297021241265, 0.20693447296577364),
+        #                       (-0.9844931733249197, -0.9305935329026733, -0.5546432084044857),
+        #                       (-0.8586221633621384, -0.3455305862905263, 1.134123935245044),
+        #                       (-1.3469501841979155, 0.7657075730836449, -0.16488069955797996))}
+        #
+        # p_1_xyz = {'symbols': ('C', 'C', 'O', 'H', 'H', 'H'), 'isotopes': (12, 12, 16, 1, 1, 1),
+        #            'coords': ((-0.4758624005470258, 0.015865899777425058, -0.11215987340300927),
+        #                       (0.9456990856850401, -0.031530842469194666, 0.2228995599390481),
+        #                       (2.0897646616994816, -0.06967555524967288, 0.492553667108967),
+        #                       (-1.08983188764878, -0.06771143046366379, 0.7892594299969324),
+        #                       (-0.7261604551815313, 0.9578749227991876, -0.6086176800339509),
+        #                       (-0.7436090040071672, -0.8048229943940851, -0.7839351036079769))}
+        #
+        # p_2_xyz = {'symbols': ('Br', 'H'), 'isotopes': (79, 1),
+        #            'coords': ((0.7644788559644482, 0.0, 0.0), (-0.7644788559644482, 0.0, 0.0))}
+        #
+        # r_1 = ARCSpecies(label='r1', smiles='[H]', xyz=r_1_xyz)
+        # r_2 = ARCSpecies(label='r2', smiles='CC(=O)Br', xyz=r_2_xyz)
+        # p_1 = ARCSpecies(label='p1', smiles='C[C](=O)', xyz=p_1_xyz)
+        # p_2 = ARCSpecies(label='p2', smiles='[Br][H]', xyz=p_2_xyz)
+        #
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_2, p_1])
+        # atom_map=rxn.atom_map
+        # self.assertEqual(atom_map[:5], [1, 2, 3, 4, 0])
+        # self.assertIn(tuple(atom_map[5:]), permutations([5, 6, 7]))
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # Change Order [H] + CC(=O)Br <=> C[C](=O) + [H][Br]
+        # r_1 = ARCSpecies(label='r1', smiles='[H]', xyz=r_1_xyz)
+        # r_2 = ARCSpecies(label='r2', smiles='CC(=O)Br', xyz=r_2_xyz)
+        # p_1 = ARCSpecies(label='p1', smiles='C[C](=O)', xyz=p_1_xyz)
+        # p_2 = ARCSpecies(label='p2', smiles='[H][Br]', xyz=p_2_xyz)
+        #
+        # rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map=rxn.atom_map
+        # self.assertEqual(atom_map[:5], [7, 0, 1, 2, 6])
+        # self.assertIn(tuple(atom_map[5:]), list(permutations([3, 4, 5])))
+        # self.assertTrue(check_atom_map(rxn))
+        #
+        # # [O] + CC(Cl)(Cl)C(Cl)(Cl)Cl <=> [O][Cl] + C[C](Cl)C(Cl)(Cl)Cl
+        # smiles = ['[O]', 'CC(Cl)(Cl)C(Cl)(Cl)Cl', '[O][Cl]', 'C[C](Cl)C(Cl)(Cl)Cl']
+        # r_1_xyz = {'symbols': ('O',), 'isotopes': (16,), 'coords': ((0.0, 0.0, 0.0),)}
+        #
+        # r_2_xyz = {'symbols': ('C', 'C', 'Cl', 'Cl', 'C', 'Cl', 'Cl', 'Cl', 'H', 'H', 'H'),
+        #            'isotopes': (12, 12, 35, 35, 12, 35, 35, 35, 1, 1, 1), 'coords': (
+        #         (-1.3340513332954889, 0.2811635614535751, -0.078045907046801),
+        #         (-0.06460593375936133, -0.5810773314093911, -0.02962891425941322),
+        #         (-0.2609310384494481, -1.7354943987581986, 1.3623405448734305),
+        #         (-0.06523629769352735, -1.6097818007913829, -1.5298182298699716),
+        #         (1.2568349080206898, 0.251354210359208, 0.09596787533379413),
+        #         (2.7373740437547514, -0.7858820942054363, 0.1510602855327231),
+        #         (1.4729373085674606, 1.396702908938121, -1.2920641361183987),
+        #         (1.2776463867390788, 1.2712465700052025, 1.5941477468638563),
+        #         (-1.3327512075949484, 0.9633461541030465, -0.9346702675682734),
+        #         (-2.235286345856216, -0.338363905821591, -0.1659562352150731),
+        #         (-1.45193049043298, 0.886786126126846, 0.8266672374741411))}
+        #
+        # p_1_xyz = {'symbols': ('O', 'Cl'), 'isotopes': (16, 35),
+        #            'coords': ((0.8407400963991551, 0.0, 0.0), (-0.8407400963991551, 0.0, 0.0))}
+        #
+        # p_2_xyz = {'symbols': ('C', 'C', 'Cl', 'C', 'Cl', 'Cl', 'Cl', 'H', 'H', 'H'),
+        #            'isotopes': (12, 12, 35, 12, 35, 35, 35, 1, 1, 1), 'coords': (
+        #         (-1.3826664358998055, -0.04852445131046896, -0.016935550260331302),
+        #         (-0.01984344739858957, 0.5351447284412386, 0.14069644461529232),
+        #         (0.06780252918727915, 2.0178457939896477, 1.0316373428560468),
+        #         (1.240695333262242, -0.22627953918952265, -0.15010504208991474),
+        #         (2.5003017492701316, 0.8385176202279041, -0.8511606324628386),
+        #         (1.8619474142609682, -0.9616513146239644, 1.3591396432655138),
+        #         (0.9630230000989414, -1.5484613928720057, -1.3347069863893728),
+        #         (-1.4535219021739985, -1.0095075283181074, 0.502205010423143),
+        #         (-2.1607091682952886, 0.6031752006499635, 0.39420249485619346),
+        #         (-1.6170290723118037, -0.20025911699469934, -1.0749727248137075))}
+        #
+        # r_1 = ARCSpecies(label='r1', smiles=smiles[0], xyz=r_1_xyz)
+        # r_2 = ARCSpecies(label='r2', smiles=smiles[1], xyz=r_2_xyz)
+        # p_1 = ARCSpecies(label='p1', smiles=smiles[2], xyz=p_1_xyz)
+        # p_2 = ARCSpecies(label='p2', smiles=smiles[3], xyz=p_2_xyz)
+        #
+        # rxn1 = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        # atom_map = rxn1.atom_map
+        # self.assertEqual(atom_map[:3],[0,2,3])
+        # self.assertIn(atom_map[3:5],[[1,4],[4,1]])
+        # self.assertEqual(atom_map[5],5)
+        # self.assertIn(atom_map[6], [6,7,8])
+        # self.assertIn(atom_map[7], [6, 7, 8])
+        # self.assertIn(atom_map[8], [6, 7, 8])
+        # self.assertIn(atom_map[9], [9, 10, 11])
+        # self.assertIn(atom_map[10], [9, 10, 11])
+        # self.assertIn(atom_map[11], [9, 10, 11])
+        # self.assertTrue(check_atom_map(rxn1))
     
     def test_map_ho2_elimination_from_peroxy_radical(self):
         """Test the map_ho2_elimination_from_peroxy_radical() function."""
diff --git a/arc/mapping/engine.py b/arc/mapping/engine.py
index 45d97ce724..893001c6bc 100644
--- a/arc/mapping/engine.py
+++ b/arc/mapping/engine.py
@@ -17,9 +17,9 @@
 from rmgpy.molecule import Molecule
 from rmgpy.species import Species
 
-import arc.rmgdb as rmgdb
 from arc.common import convert_list_index_0_to_1, extremum_list, generate_resonance_structures, logger, key_by_val
 from arc.exceptions import SpeciesError
+from arc.reaction.family import ReactionFamily, get_reaction_family_products
 from arc.species import ARCSpecies
 from arc.species.conformers import determine_chirality
 from arc.species.converter import compare_confs, sort_xyz_using_indices, translate_xyz, xyz_from_data, xyz_to_str
@@ -27,201 +27,268 @@
 from numpy import unique
 
 if TYPE_CHECKING:
-    from rmgpy.data.kinetics.family import TemplateReaction
-    from rmgpy.data.rmg import RMGDatabase
     from rmgpy.molecule.molecule import Atom
-    from rmgpy.reaction import Reaction
     from arc.reaction import ARCReaction
 
 
 RESERVED_FINGERPRINT_KEYS = ['self', 'chirality', 'label']
 
 
-def get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction: 'ARCReaction',
-                                                         rmg_reaction: 'TemplateReaction',
-                                                         ) -> Tuple[Optional[Dict[str, int]], Optional[Dict[str, int]]]:
+def get_atom_indices_of_labeled_atoms_in_a_reaction(arc_reaction: 'ARCReaction',
+                                                    ) -> Tuple[Dict[str, int], Dict[str, int]]:
     """
-    Get the RMG reaction atom labels and the corresponding 0-indexed atom indices
-    for all labeled atoms in a TemplateReaction.
+    Get the atom indices for all labeled atoms in an ARCReaction object instance.
 
     Args:
         arc_reaction (ARCReaction): An ARCReaction object instance.
-        rmg_reaction (TemplateReaction): A respective RMG family TemplateReaction object instance.
+
+    Todo:
+        - Currently only considering the first reaction for a single atom map,
+          should be extended to include all reactions and make atom_map a list of ARCReaction (call it .atom_maps ?).
 
     Returns:
-        Tuple[Optional[Dict[str, int]], Optional[Dict[str, int]]]:
-            The tuple entries relate to reactants and products.
-            Keys are labels (e.g., '*1'), values are corresponding 0-indices atoms.
-    """
-    if not hasattr(rmg_reaction, 'labeled_atoms') or not rmg_reaction.labeled_atoms:
-        return None, None
-
-    for spc in rmg_reaction.reactants + rmg_reaction.products:
-        generate_resonance_structures(object_=spc, save_order=True)
-
-    r_map, p_map = map_arc_rmg_species(arc_reaction=arc_reaction, rmg_reaction=rmg_reaction, concatenate=False)
-
-    reactant_index_dict, product_index_dict = dict(), dict()
-    reactant_atoms, product_atoms = list(), list()
-    rmg_reactant_order = [val for _, val in sorted(r_map.items(), key=lambda item: item[0])]
-    rmg_product_order = [val for _, val in sorted(p_map.items(), key=lambda item: item[0])]
-    for i in rmg_reactant_order:
-        reactant_atoms.extend([atom for atom in rmg_reaction.reactants[i].atoms])
-    for i in rmg_product_order:
-        product_atoms.extend([atom for atom in rmg_reaction.products[i].atoms])
-
-    for labeled_atom_dict, atom_list, index_dict in zip([rmg_reaction.labeled_atoms['reactants'],
-                                                         rmg_reaction.labeled_atoms['products']],
-                                                        [reactant_atoms, product_atoms],
-                                                        [reactant_index_dict, product_index_dict]):
-        for label, atom_1 in labeled_atom_dict.items():
-            for i, atom_2 in enumerate(atom_list):
-                if atom_1.id == atom_2.id:
-                    index_dict[label] = i
-                    break
+        Tuple[Dict[str, int], Dict[str, int]]: Keys are labels (e.g., '*1'),
+                                               values are corresponding 0-indexed atom indices
+                                               in the reactants and in the products.
+    """
+    product_dicts = get_reaction_family_products(arc_reaction)
+    product_dict = product_dicts[0]
+    reactant_index_dict, product_index_dict = product_dict['label_map'], dict()
+    pairs = pair_reaction_products(arc_reaction, product_dict['products'])
+    maps = dict()
+    for arc_rxn_idx, prod_idx in pairs.items():
+        maps[prod_idx] = map_two_species(arc_reaction.p_species[arc_rxn_idx],
+                                         ARCSpecies(label=f'P{prod_idx}', mol=product_dict['products'][prod_idx]),
+                                         map_type='dict',
+                                         consider_chirality=False,
+                                         )
+    fam_prods_map_to_rxn_prods = dict()
+    for i in range(len(maps.keys())):
+        for key, val in maps[i].items():
+            fam_prods_map_to_rxn_prods[key + sum([len(mol.atoms) for mol in product_dict['products'][:i]])] = (
+                    val + sum([len(spc.mol.atoms) for spc in arc_reaction.r_species[:i]]))
+    product_index_dict = {key: fam_prods_map_to_rxn_prods[val] for key, val in reactant_index_dict.items()}
     return reactant_index_dict, product_index_dict
 
 
-def map_arc_rmg_species(arc_reaction: 'ARCReaction',
-                        rmg_reaction: Union['Reaction', 'TemplateReaction'],
-                        concatenate: bool = True,
-                        ) -> Tuple[Dict[int, Union[List[int], int]], Dict[int, Union[List[int], int]]]:
+def pair_reaction_products(reaction: 'ARCReaction',
+                           products: List['Molecule'],
+                           ) -> Dict[int, int]:
     """
-    Map the species pairs in an ARC reaction to those in a respective RMG reaction
-    which is defined in the same direction.
+    Map the species pairs in an ARC reaction to those in the given product list.
+    This function assumes that resonance structures (mol_list) were generated for the ARCReaction object instance.
 
     Args:
-        arc_reaction (ARCReaction): An ARCReaction object instance.
-        rmg_reaction (Union[Reaction, TemplateReaction]): A respective RMG family TemplateReaction object instance.
-        concatenate (bool, optional): Whether to return isomorphic species as a single list (``True``, default),
-                                      or to return isomorphic species separately (``False``).
+        reaction (ARCReaction): An ARCReaction object instance.
+        products (List[ARCSpecies]): Species that correspond to the ARCReaction products that require pairing.
 
     Returns:
-        Tuple[Dict[int, Union[List[int], int]], Dict[int, Union[List[int], int]]]:
-            The first tuple entry refers to reactants, the second to products.
-            Keys are specie indices in the ARC reaction,
-            values are respective indices in the RMG reaction.
-            If ``concatenate`` is ``True``, values are lists of integers. Otherwise, values are integers.
-    """
-    if rmg_reaction.is_isomerization():
-        if concatenate:
-            return {0: [0]}, {0: [0]}
-        else:
-            return {0: 0}, {0: 0}
-    r_map, p_map = dict(), dict()
-    arc_reactants, arc_products = arc_reaction.get_reactants_and_products(arc=True)
-    for spc_map, rmg_species, arc_species in [(r_map, rmg_reaction.reactants, arc_reactants),
-                                              (p_map, rmg_reaction.products, arc_products)]:
-        for i, arc_spc in enumerate(arc_species):
-            for j, rmg_obj in enumerate(rmg_species):
-                rmg_spc = Species(molecule=[rmg_obj]) if isinstance(rmg_obj, Molecule) else rmg_obj
-                if not isinstance(rmg_spc, Species):
-                    raise ValueError(f'Expected an RMG object instances of Molecule or Species, '
-                                     f'got {rmg_obj} which is a {type(rmg_obj)}.')
-                generate_resonance_structures(object_=rmg_spc, save_order=True)
-                rmg_spc_based_on_arc_spc = Species(molecule=arc_spc.mol_list)
-                generate_resonance_structures(object_=rmg_spc_based_on_arc_spc, save_order=True)
-                if rmg_spc.is_isomorphic(rmg_spc_based_on_arc_spc, save_order=True):
-                    if i in spc_map.keys() and concatenate:
-                        spc_map[i].append(j)
-                    elif concatenate:
-                        spc_map[i] = [j]
-                    elif i not in spc_map.keys() and j not in spc_map.values():
-                        spc_map[i] = j
+        Dict[int, int]: Keys are species indices in the ARC reaction, values are respective indices in the product list.
+    """
+    if reaction.is_isomerization():
+        return {0: 0}
+    product_pairs = dict()
+    arc_products = reaction.get_reactants_and_products(arc=True)[1]
+    for i, arc_product in enumerate(arc_products):
+        found = False
+        for j, prod in enumerate(products):
+            if j not in product_pairs.values():
+                for arc_mol in arc_product.mol_list:
+                    if arc_mol.is_isomorphic(prod):
+                        product_pairs[i] = j
+                        found = True
                         break
-    if not r_map or not p_map:
-        raise ValueError(f'Could not match some of the RMG Reaction {rmg_reaction} to the ARC Reaction {arc_reaction}.')
-    return r_map, p_map
-
-
-def find_equivalent_atoms_in_reactants(arc_reaction: 'ARCReaction',
-                                       backend: str = 'ARC',
-                                       ) -> List[List[int]]:
-    """
-    Find atom indices that are equivalent in the reactants of an ARCReaction
-    in the sense that they represent degenerate reaction sites that are indifferentiable in 2D.
-    Bridges between RMG reaction templates and ARC's 3D TS structures.
-    Running indices in the returned structure relate to reactant_0 + reactant_1 + ...
-
-    Args:
-        arc_reaction ('ARCReaction'): The ARCReaction object instance.
-        backend (str, optional): Whether to use ``'QCElemental'`` or ``ARC``'s method as the backend.
-
-    Returns:
-        List[List[int]]: Entries are lists of 0-indices, each such list represents equivalent atoms.
-    """
-    rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction, backend=backend)
-    dicts = [get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(rmg_reaction=rmg_reaction,
-                                                                  arc_reaction=arc_reaction)[0]
-             for rmg_reaction in rmg_reactions]
-    equivalence_map = dict()
-    for index_dict in dicts:
-        for key, value in index_dict.items():
-            if key in equivalence_map:
-                equivalence_map[key].append(value)
-            else:
-                equivalence_map[key] = [value]
-    equivalent_indices = list(list(set(equivalent_list)) for equivalent_list in equivalence_map.values())
-    return equivalent_indices
-
-
-def get_rmg_reactions_from_arc_reaction(arc_reaction: 'ARCReaction',
-                                        backend: str = 'ARC',
-                                        db: Optional['RMGDatabase'] = None,
-                                        ) -> Optional[List['TemplateReaction']]:
-    """
-    A helper function for getting RMG reactions from an ARC reaction.
-    This function calls ``map_two_species()`` so that each species in the RMG reaction is correctly mapped
-    to the corresponding species in the ARC reaction. It does not attempt to map reactants to products.
-
-    Args:
-        arc_reaction (ARCReaction): The ARCReaction object instance.
-        backend (str, optional): Whether to use ``'QCElemental'`` or ``ARC``'s method as the backend.
-        db (RMGDatabase, optional): The RMG database instance.
-
-    Returns:
-        Optional[List[TemplateReaction]]:
-            The respective RMG TemplateReaction object instances (considering resonance structures).
-    """
-    if arc_reaction.family is None:
-        rmgdb.determine_family(reaction=arc_reaction, db=db)
-    if arc_reaction.family is None:
-        return None
-    if not arc_reaction.family.save_order:
-        raise ValueError('Must have the save_order attribute of the family set to True.')
-    rmg_reactions = arc_reaction.family.generate_reactions(reactants=[spc.mol.copy(deep=True) for spc in arc_reaction.r_species],
-                                                           products=[spc.mol.copy(deep=True) for spc in arc_reaction.p_species],
-                                                           prod_resonance=True,
-                                                           delete_labels=False,
-                                                           relabel_atoms=False,
-                                                           )
-    for rmg_reaction in rmg_reactions:
-        r_map, p_map = map_arc_rmg_species(arc_reaction=arc_reaction, rmg_reaction=rmg_reaction, concatenate=False)
-        try:
-            ordered_rmg_reactants = [rmg_reaction.reactants[r_map[i]] for i in range(len(rmg_reaction.reactants))]
-            ordered_rmg_products = [rmg_reaction.products[p_map[i]] for i in range(len(rmg_reaction.products))]
-        except KeyError:
-            logger.warning(f'Got a problematic RMG rxn from ARC rxn, trying again')
-            continue
-        mapped_rmg_reactants, mapped_rmg_products = list(), list()
-        for ordered_rmg_mols, arc_species, mapped_mols in zip([ordered_rmg_reactants, ordered_rmg_products],
-                                                              [arc_reaction.r_species, arc_reaction.p_species],
-                                                              [mapped_rmg_reactants, mapped_rmg_products],
-                                                              ):
-            for rmg_mol, arc_spc in zip(ordered_rmg_mols, arc_species):
-                mol = arc_spc.copy().mol
-                # The RMG molecule will get a random 3D conformer, don't consider chirality when mapping.
-                atom_map = map_two_species(mol, rmg_mol, map_type='dict', backend=backend, consider_chirality=False)
-                if atom_map is None:
-                    continue
-                new_atoms_list = list()
-                for i in range(len(rmg_mol.atoms)):
-                    rmg_mol.atoms[atom_map[i]].id = mol.atoms[i].id
-                    new_atoms_list.append(rmg_mol.atoms[atom_map[i]])
-                rmg_mol.atoms = new_atoms_list
-                mapped_mols.append(rmg_mol)
-        rmg_reaction.reactants, rmg_reaction.products = mapped_rmg_reactants, mapped_rmg_products
-    return rmg_reactions
+            if found:
+                break
+    if len(product_pairs.keys()) != len(arc_products):
+        raise ValueError(f'Could not match some of the products in: {reaction}\nto the given products:\n{products}')
+    return product_pairs
+
+
+
+
+
+
+
+# def get_rmg_reactions_from_arc_reaction(arc_reaction: 'ARCReaction',
+#                                         backend: str = 'ARC',
+#                                         ) -> Optional[List['TemplateReaction']]:
+#     """
+#     A helper function for getting RMG reactions from an ARC reaction.
+#     This function calls ``map_two_species()`` so that each species in the RMG reaction is correctly mapped
+#     to the corresponding species in the ARC reaction. It does not attempt to map reactants to products.
+#
+#     Args:
+#         arc_reaction (ARCReaction): The ARCReaction object instance.
+#         backend (str, optional): Whether to use ``'QCElemental'`` or ``ARC``'s method as the backend.
+#
+#     Returns:
+#         Optional[List[TemplateReaction]]:
+#             The respective RMG TemplateReaction object instances (considering resonance structures).
+#     """
+#     if arc_reaction.family is None:
+#         return None
+#     rmg_reactions = arc_reaction.family.generate_reactions(reactants=[spc.mol.copy(deep=True) for spc in arc_reaction.r_species],
+#                                                            products=[spc.mol.copy(deep=True) for spc in arc_reaction.p_species],
+#                                                            prod_resonance=True,
+#                                                            delete_labels=False,
+#                                                            relabel_atoms=False,
+#                                                            )
+#     for rmg_reaction in rmg_reactions:
+#         r_map, p_map = map_arc_rmg_species(arc_reaction=arc_reaction, rmg_reaction=rmg_reaction, concatenate=False)
+#         try:
+#             ordered_rmg_reactants = [rmg_reaction.reactants[r_map[i]] for i in range(len(rmg_reaction.reactants))]
+#             ordered_rmg_products = [rmg_reaction.products[p_map[i]] for i in range(len(rmg_reaction.products))]
+#         except KeyError:
+#             logger.warning(f'Got a problematic RMG rxn from ARC rxn, trying again')
+#             continue
+#         mapped_rmg_reactants, mapped_rmg_products = list(), list()
+#         for ordered_rmg_mols, arc_species, mapped_mols in zip([ordered_rmg_reactants, ordered_rmg_products],
+#                                                               [arc_reaction.r_species, arc_reaction.p_species],
+#                                                               [mapped_rmg_reactants, mapped_rmg_products],
+#                                                               ):
+#             for rmg_mol, arc_spc in zip(ordered_rmg_mols, arc_species):
+#                 mol = arc_spc.copy().mol
+#                 # The RMG molecule will get a random 3D conformer, don't consider chirality when mapping.
+#                 atom_map = map_two_species(mol, rmg_mol, map_type='dict', backend=backend, consider_chirality=False)
+#                 if atom_map is None:
+#                     continue
+#                 new_atoms_list = list()
+#                 for i in range(len(rmg_mol.atoms)):
+#                     rmg_mol.atoms[atom_map[i]].id = mol.atoms[i].id
+#                     new_atoms_list.append(rmg_mol.atoms[atom_map[i]])
+#                 rmg_mol.atoms = new_atoms_list
+#                 mapped_mols.append(rmg_mol)
+#         rmg_reaction.reactants, rmg_reaction.products = mapped_rmg_reactants, mapped_rmg_products
+#     return rmg_reactions
+#
+#
+# def get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction: 'ARCReaction',
+#                                                          rmg_reaction: 'TemplateReaction',
+#                                                          ) -> Tuple[Optional[Dict[str, int]], Optional[Dict[str, int]]]:
+#     """
+#     Get the RMG reaction atom labels and the corresponding 0-indexed atom indices
+#     for all labeled atoms in a TemplateReaction.
+#
+#     Args:
+#         arc_reaction (ARCReaction): An ARCReaction object instance.
+#         rmg_reaction (TemplateReaction): A respective RMG family TemplateReaction object instance.
+#
+#     Returns:
+#         Tuple[Optional[Dict[str, int]], Optional[Dict[str, int]]]:
+#             The tuple entries relate to reactants and products.
+#             Keys are labels (e.g., '*1'), values are corresponding 0-indices atoms.
+#     """
+#     if not hasattr(rmg_reaction, 'labeled_atoms') or not rmg_reaction.labeled_atoms:
+#         return None, None
+#
+#     for spc in rmg_reaction.reactants + rmg_reaction.products:
+#         generate_resonance_structures(object_=spc, save_order=True)
+#
+#     r_map, p_map = map_arc_rmg_species(arc_reaction=arc_reaction, rmg_reaction=rmg_reaction, concatenate=False)
+#
+#     reactant_index_dict, product_index_dict = dict(), dict()
+#     reactant_atoms, product_atoms = list(), list()
+#     rmg_reactant_order = [val for _, val in sorted(r_map.items(), key=lambda item: item[0])]
+#     rmg_product_order = [val for _, val in sorted(p_map.items(), key=lambda item: item[0])]
+#     for i in rmg_reactant_order:
+#         reactant_atoms.extend([atom for atom in rmg_reaction.reactants[i].atoms])
+#     for i in rmg_product_order:
+#         product_atoms.extend([atom for atom in rmg_reaction.products[i].atoms])
+#
+#     for labeled_atom_dict, atom_list, index_dict in zip([rmg_reaction.labeled_atoms['reactants'],
+#                                                          rmg_reaction.labeled_atoms['products']],
+#                                                         [reactant_atoms, product_atoms],
+#                                                         [reactant_index_dict, product_index_dict]):
+#         for label, atom_1 in labeled_atom_dict.items():
+#             for i, atom_2 in enumerate(atom_list):
+#                 if atom_1.id == atom_2.id:
+#                     index_dict[label] = i
+#                     break
+#     return reactant_index_dict, product_index_dict
+#
+#
+# def map_arc_rmg_species(arc_reaction: 'ARCReaction',
+#                         rmg_reaction: Union['Reaction', 'TemplateReaction'],
+#                         concatenate: bool = True,
+#                         ) -> Tuple[Dict[int, Union[List[int], int]], Dict[int, Union[List[int], int]]]:
+#     """
+#     Map the species pairs in an ARC reaction to those in a respective RMG reaction
+#     which is defined in the same direction.
+#
+#     Args:
+#         arc_reaction (ARCReaction): An ARCReaction object instance.
+#         rmg_reaction (Union[Reaction, TemplateReaction]): A respective RMG family TemplateReaction object instance.
+#         concatenate (bool, optional): Whether to return isomorphic species as a single list (``True``, default),
+#                                       or to return isomorphic species separately (``False``).
+#
+#     Returns:
+#         Tuple[Dict[int, Union[List[int], int]], Dict[int, Union[List[int], int]]]:
+#             The first tuple entry refers to reactants, the second to products.
+#             Keys are specied indices in the ARC reaction,
+#             values are respective indices in the RMG reaction.
+#             If ``concatenate`` is ``True``, values are lists of integers. Otherwise, values are integers.
+#     """
+#     if rmg_reaction.is_isomerization():
+#         if concatenate:
+#             return {0: [0]}, {0: [0]}
+#         else:
+#             return {0: 0}, {0: 0}
+#     r_map, p_map = dict(), dict()
+#     arc_reactants, arc_products = arc_reaction.get_reactants_and_products(arc=True)
+#     for spc_map, rmg_species, arc_species in [(r_map, rmg_reaction.reactants, arc_reactants),
+#                                               (p_map, rmg_reaction.products, arc_products)]:
+#         for i, arc_spc in enumerate(arc_species):
+#             for j, rmg_obj in enumerate(rmg_species):
+#                 rmg_spc = Species(molecule=[rmg_obj]) if isinstance(rmg_obj, Molecule) else rmg_obj
+#                 if not isinstance(rmg_spc, Species):
+#                     raise ValueError(f'Expected an RMG object instances of Molecule or Species, '
+#                                      f'got {rmg_obj} which is a {type(rmg_obj)}.')
+#                 generate_resonance_structures(object_=rmg_spc, save_order=True)
+#                 rmg_spc_based_on_arc_spc = Species(molecule=arc_spc.mol_list)
+#                 generate_resonance_structures(object_=rmg_spc_based_on_arc_spc, save_order=True)
+#                 if rmg_spc.is_isomorphic(rmg_spc_based_on_arc_spc, save_order=True):
+#                     if i in spc_map.keys() and concatenate:
+#                         spc_map[i].append(j)
+#                     elif concatenate:
+#                         spc_map[i] = [j]
+#                     elif i not in spc_map.keys() and j not in spc_map.values():
+#                         spc_map[i] = j
+#                         break
+#     if not r_map or not p_map:
+#         raise ValueError(f'Could not match some of the RMG Reaction {rmg_reaction} to the ARC Reaction {arc_reaction}.')
+#     return r_map, p_map
+#
+#
+# def find_equivalent_atoms_in_reactants(arc_reaction: 'ARCReaction',  # ?
+#                                        backend: str = 'ARC',
+#                                        ) -> List[List[int]]:
+#     """
+#     Find atom indices that are equivalent in the reactants of an ARCReaction
+#     in the sense that they represent degenerate reaction sites that are indifferentiable in 2D.
+#     Bridges between RMG reaction templates and ARC's 3D TS structures.
+#     Running indices in the returned structure relate to reactant_0 + reactant_1 + ...
+#
+#     Args:
+#         arc_reaction ('ARCReaction'): The ARCReaction object instance.
+#         backend (str, optional): Whether to use ``'QCElemental'`` or ``ARC``'s method as the backend.
+#
+#     Returns:
+#         List[List[int]]: Entries are lists of 0-indices, each such list represents equivalent atoms.
+#     """
+#     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction, backend=backend)
+#     dicts = [get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(rmg_reaction=rmg_reaction,
+#                                                                   arc_reaction=arc_reaction)[0]
+#              for rmg_reaction in rmg_reactions]
+#     equivalence_map = dict()
+#     for index_dict in dicts:
+#         for key, value in index_dict.items():
+#             if key in equivalence_map:
+#                 equivalence_map[key].append(value)
+#             else:
+#                 equivalence_map[key] = [value]
+#     equivalent_indices = list(list(set(equivalent_list)) for equivalent_list in equivalence_map.values())
+#     return equivalent_indices
 
 
 def map_two_species(spc_1: Union[ARCSpecies, Species, Molecule],
@@ -1031,8 +1098,7 @@ def make_bond_changes(rxn: 'ARCReaction',
         r_cuts: the cut products
         r_label_dict: the dictionary object the find the relevant location.
     """
-    
-    for action in rxn.family.forward_recipe.actions:
+    for action in ReactionFamily(label=rxn.family).actions:
         if action[0].lower() == "CHANGE_BOND".lower():
             indicies = r_label_dict[action[1]],r_label_dict[action[3]]
             for r_cut in r_cuts:
@@ -1064,26 +1130,51 @@ def make_bond_changes(rxn: 'ARCReaction',
                     r_cut.mol.update()
 
 
+def get_label_dict(rxn: 'ARCReaction') -> Optional[Dict[str, int]]:
+    """
+    A function that returns the labels of the products.
+
+    Args:
+        rxn: ARCReaction object
+
+    Returns:
+        Optional[Dict[str, int]]: The labels of the products.
+    """
+    products = get_reaction_family_products(rxn=rxn)
+    if len(products):
+        return products[0]['label_map']
+    return None
+
+
 def assign_labels_to_products(rxn: 'ARCReaction',
-                              p_label_dict: dict):
+                              products: List[Molecule],
+                              ):
     """
     Add the indices to the reactants and products.
 
     Args:
-        rxn: ARCReaction object to be mapped
-        p_label_dict: the labels of the products
-        Consider changing in rmgpy.
+        rxn ('ARCReaction'): The reaction to be mapped.
+        products (List[Molecule]): The products generated from the RMG family with the same atom order as the reactants.
 
     Returns:
         Adding labels to the atoms of the reactants and products, to be identified later.
     """
-
+    label_dict = get_label_dict(rxn)
+    atom_index = 0
+    for r in rxn.r_species:
+        for atom in r.mol.atoms:
+            if atom_index in label_dict.values():
+                atom.label = key_by_val(label_dict, atom_index)
+            atom_index += 1
+    product_pairs = pair_reaction_products(reaction=rxn, products=products)
     atom_index = 0
-    for product in rxn.p_species:
-        for atom in product.mol.atoms:
-            if atom_index in p_label_dict.values() and (atom.label is str or atom.label is None):
-                atom.label = key_by_val(p_label_dict,atom_index)
-            atom_index+=1
+    for product_index in range(len(products)):
+        rxn_product, fam_product = rxn.p_species[product_index], products[product_pairs[product_index]]
+        atom_map = map_two_species(spc_1=rxn_product, spc_2=fam_product, map_type='list')
+        for i, atom in enumerate(fam_product.atoms):
+            if atom_index in label_dict.values():
+                rxn_product.mol.atoms[atom_map[i]].label = key_by_val(label_dict, atom_index)
+            atom_index += 1
 
 
 def update_xyz(spcs: List[ARCSpecies]) -> List[ARCSpecies]:
@@ -1095,7 +1186,7 @@ def update_xyz(spcs: List[ARCSpecies]) -> List[ARCSpecies]:
         spcs: the scission products that needs to be updated
 
     Returns:
-        new: A newely generated copies of the ARCSpecies, with updated xyz
+        list: A newly generated copies of the ARCSpecies, with updated xyz.
     """
     new = list()
     for spc in spcs:
@@ -1125,7 +1216,7 @@ def r_cut_p_cut_isomorphic(reactant, product):
 
 def pairing_reactants_and_products_for_mapping(r_cuts: List[ARCSpecies],
                                                p_cuts: List[ARCSpecies]
-                                               )-> List[Tuple[ARCSpecies,ARCSpecies]]:
+                                               ) -> List[Tuple[ARCSpecies,ARCSpecies]]:
     """
     A function for matching reactants and products in scissored products.
 
@@ -1134,21 +1225,21 @@ def pairing_reactants_and_products_for_mapping(r_cuts: List[ARCSpecies],
         p_cuts: A list of the scissored species in the reactants
 
     Returns:
-        a list of paired reactant and products, to be sent to map_two_species.
+        list: Paired reactant and products, to be sent to map_two_species.
     """
     pairs = []
     for reactant_cut in r_cuts:
         for product_cut in p_cuts:
             if r_cut_p_cut_isomorphic(reactant_cut, product_cut):
                 pairs.append((reactant_cut, product_cut))
-                p_cuts.remove(product_cut) # Just in case there are two of the same species in the list, matching them by order.
+                p_cuts.remove(product_cut)  # Just in case there are two of the same species in the list, matching them by order.
                 break
     return pairs
 
 
 def map_pairs(pairs):
     """
-    A function that maps the mached species together
+    A function that maps the matched species together
 
     Args:
         pairs: A list of the pairs of reactants and species
@@ -1156,11 +1247,9 @@ def map_pairs(pairs):
     Returns:
         A list of the mapped species
     """
-
     maps = list()
     for pair in pairs:
         maps.append(map_two_species(pair[0], pair[1]))
-
     return maps
 
 
@@ -1171,11 +1260,11 @@ def label_species_atoms(spcs):
     Args:
         spcs: ARCSpecies object to be labeled.
     """
-    index=0
+    index = 0
     for spc in spcs:
         for atom in spc.mol.atoms:
             atom.label = str(index)
-            index+=1
+            index += 1
 
 
 def glue_maps(maps, pairs_of_reactant_and_products):
@@ -1183,11 +1272,11 @@ def glue_maps(maps, pairs_of_reactant_and_products):
     a function that joins together the maps from the parts of the reaction.
 
     Args:
-        rxn: ARCReaction that requires atom mapping
         maps: The list of all maps of the isomorphic cuts.
+        pairs_of_reactant_and_products: The pairs of the reactants and products.
 
     Returns:
-        an Atom Map of the compleate reaction.
+        list: An Atom Map of the complete reaction.
     """
     am_dict = dict()
     for _map, pair in zip(maps, pairs_of_reactant_and_products):
@@ -1229,18 +1318,21 @@ def determine_bdes_on_spc_based_on_atom_labels(spc: "ARCSpecies", bde: Tuple[int
         return False
 
 
-def cut_species_based_on_atom_indices(species: List["ARCSpecies"], bdes: List[Tuple[int, int]]) -> Optional[List["ARCSpecies"]]:
+def cut_species_based_on_atom_indices(species: List["ARCSpecies"],
+                                      bdes: List[Tuple[int, int]],
+                                      ) -> Optional[List["ARCSpecies"]]:
     """
     A function for scissoring species based on their atom indices.
+
     Args:
         species (List[ARCSpecies]): The species list that requires scission.
         bdes (List[Tuple[int, int]]): A list of the atoms between which the bond should be scissored. The atoms are described using the atom labels, and not the actuall atom positions.
+
     Returns:
         Optional[List["ARCSpecies"]]: The species list input after the scission.
     """
     if not bdes:
         return species
-    
     for bde in bdes:
         for index, spc in enumerate(species):
             if determine_bdes_on_spc_based_on_atom_labels(spc, bde):
@@ -1261,7 +1353,6 @@ def cut_species_based_on_atom_indices(species: List["ARCSpecies"], bdes: List[Tu
                     except SpeciesError:
                         return None
                 break
-                
     return species
 
 
@@ -1280,18 +1371,34 @@ def copy_species_list_for_mapping(species: List["ARCSpecies"]) -> List["ARCSpeci
     return copies
 
 
-def find_all_bdes(rxn: "ARCReaction", label_dict: dict, is_reactants: bool) -> List[Tuple[int, int]]:
+def find_all_bdes(rxn: "ARCReaction",
+                  is_reactants: bool,
+                  products: Optional[List["Molecule"]] = None,
+                  ) -> List[Tuple[int, int]]:
     """
     A function for finding all the broken(/formed) bonds during a chemical reaction, based on the atom indices.
+
     Args:
         rxn (ARCReaction): The reaction in question.
-        label_dict (dict): A dictionary of the atom indices to the atom labels.
-        is_reactants (bool): Whether or not the species list represents reactants or products.
+        is_reactants (bool): Whether the species list represents reactants or products.
+        products (List[Molecule], optional): The products generated from the RMG family with the same atom order
+                                             as the reactants. If given, the BDE values will be mapped from them
+                                             to the reaction products.
+
     Returns:
-        List[Tuple[int, int]]: A list of tuples of the form (atom_index1, atom_index2) for each broken bond. Note that these represent the atom indicies to be cut, and not final BDEs.
+        List[Tuple[int, int]]: A list of tuples of the form (atom_index1, atom_index2) for each broken bond.
+                               Note that these represent the atom indices to be cut, and not final BDEs.
     """
+    label_dict = get_label_dict(rxn)
+    if not is_reactants:
+        product_pairs = pair_reaction_products(reaction=rxn, products=products) if products is not None else None
+    print(label_dict)
     bdes = list()
-    for action in rxn.family.forward_recipe.actions:
-        if action[0].lower() == ("break_bond" if is_reactants else "form_bond"):
-            bdes.append((label_dict[action[1]] + 1, label_dict[action[3]] + 1))
+    if rxn.family is not None:
+        for action in ReactionFamily(rxn.family).actions:
+            print(action)
+            if (action[0].lower() == "break_bond" and is_reactants
+                    or action[0].lower() == "form_bond" and not is_reactants):
+                print(f'appending {action[1]} and {action[3]}: {(label_dict[action[1]] + 1, label_dict[action[3]] + 1)}')
+                bdes.append((label_dict[action[1]] + 1, label_dict[action[3]] + 1))
     return bdes
diff --git a/arc/mapping/engine_test.py b/arc/mapping/engine_test.py
index eaf6cd2368..f56eb4fd3c 100644
--- a/arc/mapping/engine_test.py
+++ b/arc/mapping/engine_test.py
@@ -7,15 +7,11 @@
 
 import unittest
 import numpy as np
-from rmgpy.data.rmg import RMGDatabase
 from random import shuffle
 import itertools
 
-from arc.common import _check_r_n_p_symbols_between_rmg_and_arc_rxns
-from arc.species import ARCSpecies
 from arc.mapping.engine import *
 from arc.reaction import ARCReaction
-from arc.rmgdb import load_families_only, determine_family
 
 from arc.species.vectors import calculate_dihedral_angle
 
@@ -35,68 +31,28 @@ def setUpClass(cls):
         """
         A method that is run before all unit tests in this class.
         """
-        cls.db = RMGDatabase()
-        load_families_only(cls.db, "all")
         cls.maxDiff = None
 
-        smiles = ['CC(C)F', '[CH3]', 'C[CH](C)', 'CF']
-        
-        r_1_1_xyz = {'symbols': ('C', 'C', 'C', 'F', 'H', 'H', 'H', 'H', 'H', 'H', 'H'),
-         'isotopes': (12, 12, 12, 19, 1, 1, 1, 1, 1, 1, 1),
-         'coords': ((1.2509680857915237, 0.00832885083067477, -0.28594855682006387),
-                    (-0.08450322338173592, -0.5786110309038947, 0.12835305965368538),
-                    (-1.196883483105121, 0.4516770584363101, 0.10106807955582568),
-                    (0.03212452836861426, -1.0465351442062332, 1.402047416169314),
-                    (1.2170230403876368, 0.39373449465586885, -1.309310880313081),
-                    (1.5446944155971303, 0.8206316657310906, 0.38700047363833845),
-                    (2.0327466889922805, -0.7555292157466509, -0.22527487012253536),
-                    (-0.3397419937928473, -1.4280299782557704, -0.5129583662636836),
-                    (-0.9791793765226446, 1.2777482351478369, 0.786037216866474),
-                    (-1.340583396165929, 0.8569620299504027, -0.9049411765144166),
-                    (-2.1366652861689137, -0.00037696563964776297, 0.43392760415012316))}
-
-        r_2_1_xyz = {'symbols': ('C', 'H', 'H', 'H'),
-        'isotopes': (12, 1, 1, 1),
-        'coords' : ((3.3746019998564553e-09, 5.828827384106545e-09, -4.859105107686622e-09),
-                    (1.0669051052331406, -0.17519582095514982, 0.05416492980439295),
-                    (-0.6853171627400634, -0.8375353626879753, -0.028085652887100996),
-                    (-0.3815879458676787, 1.0127311778142964, -0.026079272058187608))}
-
-        p_1_1_xyz = {'symbols': ('C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H'),
-        'isotopes': (12, 12, 12, 1, 1, 1, 1, 1, 1, 1),
-        'coords':  ((-1.288730238258946, 0.06292843803165035, 0.10889818910854648),
-                    (0.01096160773224897, -0.45756396262445836, -0.3934214957819532),
-                    (1.2841030977199492, 0.11324607936811129, 0.12206176848573647),
-                    (-1.4984446521053447, 1.0458196461796345, -0.3223873567509909),
-                    (-1.2824724918369017, 0.14649429503996203, 1.1995362776757934),
-                    (-2.098384694966955, -0.616646552269074, -0.17318515188247927),
-                    (0.027360233461550892, -1.0601383387124987, -1.2952225290380646),
-                    (2.122551165381095, -0.534098313164123, -0.15158596254231563),
-                    (1.2634262459696732, 0.19628891975881263, 1.2125616721427255), 
-                    (1.4596297269035956, 1.1036697883919826, -0.307255411416999))}
-
-        p_2_1_xyz = {'symbols': ('C', 'F', 'H', 'H', 'H'),
-        'isotopes': (12, 19, 1, 1, 1),
-        'coords':  ((-0.060384822736851786, 0.004838867136375763, -0.004814368798794687),
-                    (1.2877092002693546, -0.10318918150563985, 0.10266661058725791),
-                    (-0.2965861926821434, 0.9189121874074381, -0.5532990701789506),
-                    (-0.44047773762823295, -0.8660709320146035, -0.5425894744224189),
-                    (-0.49026044722212864, 0.04550905897643097, 0.9980363028129072))}
-        cls.r_1 = ARCSpecies(label='r1', smiles=smiles[0],xyz=r_1_1_xyz )
-        cls.r_2 = ARCSpecies(label='r2', smiles=smiles[1],xyz=r_2_1_xyz)
-        cls.p_1 = ARCSpecies(label='p1', smiles=smiles[2],xyz=p_1_1_xyz)
-        cls.p_2 = ARCSpecies(label='p2', smiles=smiles[3],xyz=p_2_1_xyz)
-
-        cls.r_1_1 = ARCSpecies(label='r1', smiles=smiles[0],xyz=r_1_1_xyz )
-        cls.r_2_2 = ARCSpecies(label='r2', smiles=smiles[1],xyz=r_2_1_xyz)
-        cls.p_1_1 = ARCSpecies(label='p1', smiles=smiles[2],xyz=p_1_1_xyz)
-        cls.p_2_2 = ARCSpecies(label='p2', smiles=smiles[3],xyz=p_2_1_xyz)
-
-        cls.rxn_1 = ARCReaction(r_species=[cls.r_1, cls.r_2], p_species=[cls.p_1, cls.p_2])
-        cls.rxn_1.determine_family(cls.db)
-        cls.rmg_reactions_rxn_1 = get_rmg_reactions_from_arc_reaction(arc_reaction=cls.rxn_1, backend="ARC")
-        cls.r_label_dict_rxn_1, cls.p_label_dict_rxn_1 = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=cls.rxn_1,
-                                                                                        rmg_reaction=cls.rmg_reactions_rxn_1[0])
+        smiles = ['[C]#CF', 'C#N', 'C#CF', '[C]#N']
+        r_1_xyz = {'symbols': ('C', 'C', 'F'), 'isotopes': (12, 12, 19),
+                   'coords': ((-1.4743294980458657, -0.0015578181856664775, 0.0),
+                              (0.06566963887880228, 6.93883492559459e-05, 0.0),
+                              (1.4086598591670647, 0.0014884298364102333, 0.0))}
+        r_2_xyz = {'symbols': ('C', 'N', 'H'), 'isotopes': (12, 14, 1),
+                   'coords': ((-0.03166549265366707, 0.00027268185540903927, 0.0),
+                              (1.1282915045547195, -0.009715961185409256, 0.0),
+                              (-1.096626011901052, 0.009443279330001001, 0.0))}
+        p_1_xyz = {'symbols': ('C', 'C', 'F', 'H'), 'isotopes': (12, 12, 19, 1),
+                   'coords': ((-0.6556450958206512, 0.008288859693035082, 0.041287880045658594),
+                              (0.5194805538847015, -0.006567413538153382, 0.28295662316778103),
+                              (1.8344056155700479, -0.023191047733068296, 0.5533756165580456),
+                              (-1.6982410736345843, 0.0214696015778594, -0.17312568563836497))}
+        p_2_xyz = {'symbols': ('C', 'N'), 'isotopes': (12, 14), 'coords': ((0.0, 0.0, 0.735), (0.0, 0.0, -0.735))}
+
+        cls.r_1 = ARCSpecies(label='r1', smiles=smiles[0], xyz=r_1_xyz)
+        cls.r_2 = ARCSpecies(label='r2', smiles=smiles[1], xyz=r_2_xyz)
+        cls.p_1 = ARCSpecies(label='p1', smiles=smiles[2], xyz=p_1_xyz)
+        cls.p_2 = ARCSpecies(label='p2', smiles=smiles[3], xyz=p_2_xyz)
 
         cls.spc1 = ARCSpecies(label="Test_is_isomorphic_1",smiles="C(CO)CC")
         cls.spc2 = ARCSpecies(label="Test_is_isomorphic_2",smiles="OCCCC")
@@ -134,15 +90,12 @@ def setUpClass(cls):
                                               (0.7709290243761263, -0.38422053705817527, 1.4054470816682596),
                                               (1.337910696892115, -1.3171321272490044, 0.001256204546378134),
                                               (2.595292874972368, 0.5254618254772234, 0.4066018700054956))})
-
-    
         cls.ch4_xyz = {'symbols': ('C', 'H', 'H', 'H', 'H'), 'isotopes': (12, 1, 1, 1, 1),
                        'coords': ((-5.45906343962835e-10, 4.233517924761169e-10, 2.9505240956083194e-10),
                                   (-0.6505520089868748, -0.7742801979689132, -0.4125187934483119),
                                   (-0.34927557824779626, 0.9815958255612931, -0.3276823191685369),
                                   (-0.022337921721882443, -0.04887374527620588, 1.0908766524267022),
                                   (1.0221655095024578, -0.15844188273952128, -0.350675540104908))}
-
         cls.ch3cl_xyz = {
             "symbols": ("Cl", "C", "H", "H", "H"),
             "isotopes": (35, 12, 1, 1, 1),
@@ -151,10 +104,7 @@ def setUpClass(cls):
                 (-0.13902319255720844, -0.005942522549225256, 0.0025040105508790877),
                 (-0.48751519000626353, -0.5782116958350602, -0.8600292104425608),
                 (-0.45894137315516464, -0.4942789247294056, 0.9255869621295756),
-                (-0.540565317573775, 1.0089280316586664, -0.038774361328407066),
-            ),
-        }
-
+                (-0.540565317573775, 1.0089280316586664, -0.038774361328407066))}
         cls.ch3_xyz_2 = {
             "symbols": ("C", "H", "H", "H"),
             "isotopes": (12, 1, 1, 1),
@@ -162,18 +112,12 @@ def setUpClass(cls):
                 (3.3746019998564553e-09, 5.828827384106545e-09, -4.859105107686622e-09),
                 (1.0669051052331406, -0.17519582095514982, 0.05416492980439295),
                 (-0.6853171627400634, -0.8375353626879753, -0.028085652887100996),
-                (-0.3815879458676787, 1.0127311778142964, -0.026079272058187608),
-            ),
-        }
-
+                (-0.3815879458676787, 1.0127311778142964, -0.026079272058187608))}
         cls.h_rad_xyz = {"symbols": ("H",), "isotopes": (1,), "coords": ((0, 0, 0),)}
-
         cls.hcl_xyz = {
             "symbols": ("H", "Cl"),
             "isotopes": (1, 35),
-            "coords": ((0.6878248644303301, 0.0, 0.0), (-0.6878248644303301, 0.0, 0.0)),
-        }
-
+            "coords": ((0.6878248644303301, 0.0, 0.0), (-0.6878248644303301, 0.0, 0.0))}
         cls.ch4_xyz = {
             "symbols": ("C", "H", "H", "H", "H"),
             "isotopes": (12, 1, 1, 1, 1),
@@ -182,10 +126,7 @@ def setUpClass(cls):
                 (-0.6505520089868748, -0.7742801979689132, -0.4125187934483119),
                 (-0.34927557824779626, 0.9815958255612931, -0.3276823191685369),
                 (-0.022337921721882443, -0.04887374527620588, 1.0908766524267022),
-                (1.0221655095024578, -0.15844188273952128, -0.350675540104908),
-            ),
-        }
-
+                (1.0221655095024578, -0.15844188273952128, -0.350675540104908))}
         cls.ch4_xyz_diff_order = """H      -0.65055201   -0.77428020   -0.41251879
                                     H      -0.34927558    0.98159583   -0.32768232
                                     C      -0.00000000    0.00000000    0.00000000
@@ -541,16 +482,40 @@ def setUpClass(cls):
                             H      -1.04996634   -0.37234114    0.91874740
                             H       1.36260637    0.37153887   -0.86221771"""
 
+    def test_get_atom_indices_of_labeled_atoms_in_a_reaction(self):
+        """Test getting atom indices of labeled atoms in a reaction"""
+        atom_indices = get_atom_indices_of_labeled_atoms_in_a_reaction(self.arc_reaction_1)
+        self.assertEqual(atom_indices, ({'*1': 0, '*2': 1, '*3': 5}, {'*1': 0, '*2': 1, '*3': 7}))
+
+        atom_indices = get_atom_indices_of_labeled_atoms_in_a_reaction(self.arc_reaction_2)
+        print(atom_indices)
+        self.assertEqual(atom_indices, ({'*1': 0, '*2': 3, '*3': 11}, {'*1': 0, '*2': 3, '*3': 16}))
+
+    def test_pair_reaction_products(self):
+        """Test pairing reaction and products"""
+        products = [Molecule(smiles='[CH3]'), Molecule(smiles='O')]
+        product_pairs = pair_reaction_products(self.arc_reaction_1, products)
+        self.assertEqual(product_pairs, {0: 0, 1: 1})
+
+        product_pairs = pair_reaction_products(self.arc_reaction_1, [products[1], products[0]])
+        self.assertEqual(product_pairs, {0: 1, 1: 0})
+
+        rxn_1 = ARCReaction(label='H2NN(T) + N2H4 <=> N2H3 + N2H3',
+                            r_species=[ARCSpecies(label='H2NN(T)', smiles='N[N]'),
+                                       ARCSpecies(label='N2H4', smiles='NN')],
+                            p_species=[ARCSpecies(label='N2H3', smiles='N[NH]')])
+        prod_mol = Molecule(smiles='N[NH]')
+        product_pairs = pair_reaction_products(rxn_1, [prod_mol, prod_mol])
+        self.assertEqual(product_pairs, {0: 0, 1: 1})
 
     def test_assign_labels_to_products(self):
+        """Test assigning labels to products based on the atom map of the reaction"""
         rxn_1_test = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2])
-        assign_labels_to_products(rxn_1_test, self.p_label_dict_rxn_1)
-        index = 0
-        for product in rxn_1_test.p_species:
-            for atom in product.mol.atoms:
-                if not isinstance(atom.label, str) or atom.label != "":
-                    self.assertEqual(self.p_label_dict_rxn_1[atom.label], index)
-                index+=1
+        assign_labels_to_products(rxn_1_test, rxn_1_test.get_family_products())
+        self.assertEqual([atom.label for atom in rxn_1_test.r_species[0].mol.atoms], ['*3', '', ''])
+        self.assertEqual([atom.label for atom in rxn_1_test.r_species[1].mol.atoms], ['*1', '', '*2'])
+        self.assertEqual([atom.label for atom in rxn_1_test.p_species[0].mol.atoms], ['*3', '', '*1', ''])
+        self.assertEqual([atom.label for atom in rxn_1_test.p_species[1].mol.atoms], ['', '*2'])
 
     def test_inc_vals(self):
         """Test creating an atom map via map_two_species() and incrementing all values"""
@@ -561,49 +526,44 @@ def test_inc_vals(self):
 
     def test_label_species_atoms(self):
         rxn_1_test = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2])
-        rxn_1_test.determine_family(self.db)
-        assign_labels_to_products(rxn_1_test, self.p_label_dict_rxn_1)
-        
+        assign_labels_to_products(rxn_1_test)
         reactants, products = copy_species_list_for_mapping(rxn_1_test.r_species), copy_species_list_for_mapping(rxn_1_test.p_species)
-
         label_species_atoms(reactants)
         label_species_atoms(products)
-
         index = 0
         for reactant in reactants:
             for atom in reactant.mol.atoms:
                 self.assertEqual(atom.label,str(index))
-                index +=1
-
+                index += 1
         index = 0
         for product in products:
             for atom in product.mol.atoms:
-                self.assertEqual(atom.label,str(index))
-                index +=1
+                self.assertEqual(atom.label, str(index))
+                index += 1
 
     def test_cut_species_based_on_atom_indices(self):
         """test the cut_species_for_mapping function"""
-        rxn_1_test = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2])
-        rxn_1_test.determine_family(self.db)
-        reactants, products = copy_species_list_for_mapping(rxn_1_test.r_species), copy_species_list_for_mapping(rxn_1_test.p_species)
+        rxn_1_test = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2],
+                                 rmg_family_set=['H_Abstraction'])
+        reactants = copy_species_list_for_mapping(rxn_1_test.r_species)
+        products = copy_species_list_for_mapping(rxn_1_test.p_species)
         label_species_atoms(reactants), label_species_atoms(products)
-        
-        r_bdes, p_bdes = find_all_bdes(rxn_1_test, self.r_label_dict_rxn_1, True), find_all_bdes(rxn_1_test, self.p_label_dict_rxn_1, False)
-
+        r_bdes, p_bdes = find_all_bdes(rxn_1_test, True), find_all_bdes(rxn_1_test, False)
+        print(r_bdes, p_bdes)
         r_cuts = cut_species_based_on_atom_indices(reactants, r_bdes)
         p_cuts = cut_species_based_on_atom_indices(products, p_bdes)
+        print([a.mol for a in r_cuts], [a.mol for a in p_cuts])
 
+        self.assertIn('[C]#CF', [r_cut.mol.copy(deep=True).smiles for r_cut in r_cuts])
+        self.assertIn('[C]#N', [r_cut.mol.copy(deep=True).smiles for r_cut in r_cuts])
+        self.assertIn('[H]', [r_cut.mol.copy(deep=True).smiles for r_cut in r_cuts])
+        self.assertIn('[C]#CF', [p_cut.mol.copy(deep=True).smiles for p_cut in p_cuts])
+        self.assertIn('[C]#N', [p_cut.mol.copy(deep=True).smiles for p_cut in p_cuts])
+        self.assertIn('[H]', [p_cut.mol.copy(deep=True).smiles for p_cut in p_cuts])
 
-        self.assertIn("C[CH]C", [r_cut.mol.copy(deep=True).smiles for r_cut in r_cuts])
-        self.assertIn("[F]", [r_cut.mol.copy(deep=True).smiles for r_cut in r_cuts])
-        self.assertIn("[CH3]", [r_cut.mol.copy(deep=True).smiles for r_cut in r_cuts])
-        self.assertIn("C[CH]C", [p_cut.mol.copy(deep=True).smiles for p_cut in p_cuts])
-        self.assertIn("[F]", [p_cut.mol.copy(deep=True).smiles for p_cut in p_cuts])
-        self.assertIn("[CH3]", [p_cut.mol.copy(deep=True).smiles for p_cut in p_cuts])
-
-        spc = ARCSpecies(label="test", smiles="CNC", bdes = [(1, 2), (2, 3)])
+        spc = ARCSpecies(label="test", smiles="CNC", bdes=[(1, 2), (2, 3)])
         for i, a in enumerate(spc.mol.atoms):
-            a.label=str(i)
+            a.label = str(i)
         cuts = cut_species_based_on_atom_indices([spc], [(1, 2), (2, 3)])
         self.assertEqual(len(cuts), 3)
         for cut in cuts:
@@ -613,24 +573,21 @@ def test_cut_species_based_on_atom_indices(self):
         h2 = ARCSpecies(label="H2", smiles="[H][H]")
         label_species_atoms([h2])
 
-        cuts =  cut_species_based_on_atom_indices([h2], [(1, 2)])
+        cuts = cut_species_based_on_atom_indices([h2], [(1, 2)])
         self.assertEqual(len(cuts), 2)
         for cut in cuts:
             self.assertEqual(cut.get_xyz()["symbols"], ('H',))
-        
-        spcs = [ARCSpecies(label="r", smiles = 'O=C(O)CCF')]
+
+        spcs = [ARCSpecies(label="r", smiles='O=C(O)CCF')]
         label_species_atoms(spcs)
         cuts = cut_species_based_on_atom_indices(spcs, [(6, 5), (4, 2), (3, 7)])
         self.assertEqual(len(cuts), 4)
 
     def test_r_cut_p_cut_isomorphic(self):
         rxn_1_test = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2])
-        rxn_1_test.determine_family(self.db)
         reactants, products = copy_species_list_for_mapping(rxn_1_test.r_species), copy_species_list_for_mapping(rxn_1_test.p_species)
         label_species_atoms(reactants), label_species_atoms(products)
-        
-        r_bdes, p_bdes = find_all_bdes(rxn_1_test, self.r_label_dict_rxn_1, True), find_all_bdes(rxn_1_test, self.p_label_dict_rxn_1, False)
-
+        r_bdes, p_bdes = find_all_bdes(rxn_1_test, True), find_all_bdes(rxn_1_test, False)
         r_cuts = cut_species_based_on_atom_indices(reactants, r_bdes)
         p_cuts = cut_species_based_on_atom_indices(products, p_bdes)
 
@@ -647,12 +604,9 @@ def test_r_cut_p_cut_isomorphic(self):
     def test_pairing_reactants_and_products_for_mapping(self):
         smiles = ["[F]", "C[CH]C", "[CH3]"]
         rxn_1_test = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2])
-        rxn_1_test.determine_family(self.db)
         reactants, products = copy_species_list_for_mapping(rxn_1_test.r_species), copy_species_list_for_mapping(rxn_1_test.p_species)
         label_species_atoms(reactants), label_species_atoms(products)
-        
-        r_bdes, p_bdes = find_all_bdes(rxn_1_test, self.r_label_dict_rxn_1, True), find_all_bdes(rxn_1_test, self.p_label_dict_rxn_1, False)
-
+        r_bdes, p_bdes = find_all_bdes(rxn_1_test, True), find_all_bdes(rxn_1_test, False)
         r_cuts = cut_species_based_on_atom_indices(reactants, r_bdes)
         p_cuts = cut_species_based_on_atom_indices(products, p_bdes)
 
@@ -663,17 +617,11 @@ def test_pairing_reactants_and_products_for_mapping(self):
             self.assertIn(str(pair[0].mol.copy(deep=True).to_smiles()), smiles)
             smiles.remove(pair[0].mol.copy(deep=True).to_smiles())
 
-    def test_map_pairs(self):
+    def test_map_pairs(self):  # H abs reverse 1st
         rxn_1_test = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2])
-        rxn_1_test.determine_family(self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn_1_test, backend="ARC")
-        r_label_dict, p_label_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn_1_test,
-                                                                                          rmg_reaction=rmg_reactions[0])
         reactants, products = copy_species_list_for_mapping(rxn_1_test.r_species), copy_species_list_for_mapping(rxn_1_test.p_species)
         label_species_atoms(reactants), label_species_atoms(products)
-        
-        r_bdes, p_bdes = find_all_bdes(rxn_1_test, r_label_dict, True), find_all_bdes(rxn_1_test, p_label_dict, False)
-
+        r_bdes, p_bdes = find_all_bdes(rxn_1_test, True), find_all_bdes(rxn_1_test, False)
         r_cuts = cut_species_based_on_atom_indices(reactants, r_bdes)
         p_cuts = cut_species_based_on_atom_indices(products, p_bdes)
         pairs_of_reactant_and_products = pairing_reactants_and_products_for_mapping(r_cuts, p_cuts)
@@ -695,16 +643,10 @@ def test_map_pairs(self):
     
     def test_glue_maps(self):
         rxn_1_test = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2])
-        rxn_1_test.determine_family(self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn_1_test, backend="ARC")
-        r_label_dict, p_label_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn_1_test,
-                                                                                      rmg_reaction=rmg_reactions[0])
-        assign_labels_to_products(rxn_1_test, p_label_dict)
+        assign_labels_to_products(rxn_1_test)
         reactants, products = copy_species_list_for_mapping(rxn_1_test.r_species), copy_species_list_for_mapping(rxn_1_test.p_species)
         label_species_atoms(reactants), label_species_atoms(products)
-        
-        r_bdes, p_bdes = find_all_bdes(rxn_1_test, r_label_dict, True), find_all_bdes(rxn_1_test, p_label_dict, False)
-
+        r_bdes, p_bdes = find_all_bdes(rxn_1_test, True), find_all_bdes(rxn_1_test, False)
         r_cuts = cut_species_based_on_atom_indices(reactants, r_bdes)
         p_cuts = cut_species_based_on_atom_indices(products, p_bdes)
         pairs_of_reactant_and_products = pairing_reactants_and_products_for_mapping(r_cuts, p_cuts)
@@ -716,213 +658,205 @@ def test_glue_maps(self):
         for index, value in enumerate(atom_map):
             self.assertEqual(atoms_r[index].symbol, atoms_p[value].symbol)
 
-    def test_get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(self):
-        """Test the get_atom_indices_of_labeled_atoms_in_an_rmg_reaction() function."""
-        determine_family(self.arc_reaction_1, db=self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.arc_reaction_1, db=self.db)
-        r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.arc_reaction_1,
-                                                                                      rmg_reaction=rmg_reactions[0])
-        self.assertEqual(r_dict['*1'], 0)
-        self.assertIn(r_dict['*2'], [1, 2, 3, 4])
-        self.assertEqual(r_dict['*3'], 5)
-        self.assertEqual(p_dict['*1'], 0)
-        self.assertIn(p_dict['*2'], [5, 6])
-        self.assertEqual(p_dict['*3'], 4)
-        self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.arc_reaction_1, rmg_reactions))
-
-        determine_family(self.arc_reaction_2, db=self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.arc_reaction_2, db=self.db)
-        r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.arc_reaction_2,
-                                                                                      rmg_reaction=rmg_reactions[0])
-        self.assertIn(r_dict['*1'], [0, 2])
-        self.assertIn(r_dict['*2'], [3, 4, 5, 8, 9, 10])
-        self.assertEqual(r_dict['*3'], 11)
-        self.assertEqual(p_dict['*1'], 0)
-        self.assertIn(p_dict['*2'], [11, 12, 13])
-        self.assertEqual(p_dict['*3'], 10)
-        self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.arc_reaction_2, rmg_reactions))
-
-        determine_family(self.arc_reaction_4, db=self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.arc_reaction_4, db=self.db)
-        r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.arc_reaction_4,
-                                                                                      rmg_reaction=rmg_reactions[0])
-        self.assertEqual(r_dict['*1'], 0)
-        self.assertEqual(r_dict['*2'], 2)
-        self.assertIn(r_dict['*3'], [7, 8])
-        self.assertEqual(p_dict['*1'], 0)
-        self.assertEqual(p_dict['*2'], 2)
-        self.assertIn(p_dict['*3'], [3, 4, 5])
-        self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.arc_reaction_4, rmg_reactions))
-
-        determine_family(self.rxn_2a, db=self.db)
-        for atom, symbol in zip(self.rxn_2a.r_species[0].mol.atoms, ['C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H']):
-            self.assertEqual(atom.symbol, symbol)
-        self.assertEqual(self.rxn_2a.r_species[0].mol.atoms[0].radical_electrons, 0)
-        self.assertEqual(self.rxn_2a.r_species[0].mol.atoms[1].radical_electrons, 1)
-        self.assertEqual(self.rxn_2a.r_species[0].mol.atoms[2].radical_electrons, 0)
-        self.assertEqual(self.rxn_2a.p_species[0].mol.atoms[0].radical_electrons, 0)
-        self.assertEqual(self.rxn_2a.p_species[0].mol.atoms[1].radical_electrons, 0)
-        self.assertEqual(self.rxn_2a.p_species[0].mol.atoms[2].radical_electrons, 1)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.rxn_2a, db=self.db)
-        r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.rxn_2a,
-                                                                                      rmg_reaction=rmg_reactions[0])
-        self.assertEqual(r_dict['*1'], 1)
-        self.assertIn(r_dict['*2'], [0, 2])
-        self.assertIn(r_dict['*3'], [4, 5, 6, 7, 8, 9])
-        self.assertEqual(p_dict['*1'], 1)
-        self.assertEqual(p_dict['*2'], 2)
-        self.assertIn(p_dict['*3'], [3, 6])
-        self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.rxn_2a, rmg_reactions))
-
-        determine_family(self.rxn_2b, db=self.db)
-        for atom, symbol in zip(self.rxn_2b.r_species[0].mol.atoms, ['C', 'C', 'H', 'H', 'H', 'H', 'C', 'H', 'H', 'H']):
-            self.assertEqual(atom.symbol, symbol)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.rxn_2b, db=self.db)
-        r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.rxn_2b,
-                                                                                      rmg_reaction=rmg_reactions[0])
-        self.assertEqual(r_dict['*1'], 1)
-        self.assertIn(r_dict['*2'], [0, 6])
-        self.assertIn(r_dict['*3'], [3, 4, 5, 7, 8, 9])
-        self.assertEqual(p_dict['*1'], 1)
-        self.assertEqual(p_dict['*2'], 2)
-        self.assertIn(p_dict['*3'], [3, 6])
-        self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.rxn_2b, rmg_reactions))
-
-        # C3H6O + C4H9O <=> C3H5O + C4H10O
-        r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O')
-        r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO')
-        p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O')
-        p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO')
-        rxn_1 = ARCReaction(reactants=['C3H6O', 'C4H9O'], products=['C3H5O', 'C4H10O'],
-                            r_species=[r_1, r_2], p_species=[p_1, p_2])
-        determine_family(rxn_1, db=self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn_1, db=self.db)
-        for rmg_reaction in rmg_reactions:
-            r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn_1,
-                                                                                          rmg_reaction=rmg_reaction)
-            for d in [r_dict, p_dict]:
-                self.assertEqual(len(list(d.keys())), 3)
-                keys = list(d.keys())
-                for label in ['*1', '*2', '*3']:
-                    self.assertIn(label, keys)
-        self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(rxn_1, rmg_reactions))
-
-        p_1 = ARCSpecies(label='C3H5O', smiles='CC=C[O]')  # Use a wrong resonance structure and repeat the above.
-        rxn_2 = ARCReaction(reactants=['C3H6O', 'C4H9O'], products=['C3H5O', 'C4H10O'],
-                            r_species=[r_1, r_2], p_species=[p_1, p_2])
-        determine_family(rxn_2, db=self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn_2, db=self.db)
-        for rmg_reaction in rmg_reactions:
-            r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn_2,
-                                                                                  rmg_reaction=rmg_reaction)
-            for d in [r_dict, p_dict]:
-                self.assertEqual(len(list(d.keys())), 3)
-                keys = list(d.keys())
-                for label in ['*1', '*2', '*3']:
-                    self.assertIn(label, keys)
-        self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(rxn_2, rmg_reactions))
-
-        # C3H6O + C4H9O <=> C3H5O + C4H10O
-        r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O', xyz=self.c3h6o_xyz)
-        r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO', xyz=self.c4h9o_xyz)
-        p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=self.c3h5o_xyz)
-        p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=self.c4h10o_xyz)
-        rxn_3 = ARCReaction(reactants=['C3H6O', 'C4H9O'], products=['C3H5O', 'C4H10O'],
-                            r_species=[r_1, r_2], p_species=[p_1, p_2])
-        determine_family(rxn_3, db=self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn_3, db=self.db)
-        r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn_3,
-                                                                                      rmg_reaction=rmg_reactions[0])
-        self.assertEqual(r_dict, {'*3': 10, '*1': 1, '*2': 7})
-        self.assertEqual(p_dict, {'*1': 1, '*3': 9, '*2': 16})
-        self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(rxn_3, rmg_reactions))
-
-
-    def test_map_arc_rmg_species(self):
-        """Test the map_arc_rmg_species() function."""
-        r_map, p_map = map_arc_rmg_species(arc_reaction=ARCReaction(r_species=[ARCSpecies(label='CCjC', smiles='C[CH]C')],
-                                                                            p_species=[ARCSpecies(label='CjCC', smiles='[CH2]CC')]),
-                                                   rmg_reaction=Reaction(reactants=[Species(smiles='C[CH]C')],
-                                                                         products=[Species(smiles='[CH2]CC')]),
-                                                   concatenate=False)
-        self.assertEqual(r_map, {0: 0})
-        self.assertEqual(p_map, {0: 0})
-
-        r_map, p_map = map_arc_rmg_species(arc_reaction=ARCReaction(r_species=[ARCSpecies(label='CCjC', smiles='C[CH]C')],
-                                                                            p_species=[ARCSpecies(label='CjCC', smiles='[CH2]CC')]),
-                                                   rmg_reaction=Reaction(reactants=[Species(smiles='C[CH]C')],
-                                                                         products=[Species(smiles='[CH2]CC')]))
-        self.assertEqual(r_map, {0: [0]})
-        self.assertEqual(p_map, {0: [0]})
-
-        r_map, p_map = map_arc_rmg_species(arc_reaction=self.arc_reaction_1, rmg_reaction=self.rmg_reaction_1)
-        self.assertEqual(r_map, {0: [0], 1: [1]})
-        self.assertEqual(p_map, {0: [0], 1: [1]})
-
-        r_map, p_map = map_arc_rmg_species(arc_reaction=self.arc_reaction_1, rmg_reaction=self.rmg_reaction_2)
-        self.assertEqual(r_map, {0: [1], 1: [0]})
-        self.assertEqual(p_map, {0: [0], 1: [1]})
-
-        r_map, p_map = map_arc_rmg_species(arc_reaction=self.arc_reaction_3, rmg_reaction=self.rmg_reaction_3)
-        self.assertEqual(r_map, {0: [0, 1], 1: [0, 1]})
-        self.assertEqual(p_map, {0: [0]})
-
-        rmg_reaction_1 = Reaction(reactants=[Species(smiles='N'), Species(smiles='[H]')],
-                                  products=[Species(smiles='[NH2]'), Species(smiles='[H][H]')])
-        rmg_reaction_2 = Reaction(reactants=[Species(smiles='[H]'), Species(smiles='N')],
-                                  products=[Species(smiles='[H][H]'), Species(smiles='[NH2]')])
-        rmg_reaction_3 = Reaction(reactants=[Species(smiles='N'), Species(smiles='[H]')],
-                                  products=[Species(smiles='[H][H]'), Species(smiles='[NH2]')])
-        arc_reaction = ARCReaction(r_species=[ARCSpecies(label='NH3', smiles='N'), ARCSpecies(label='H', smiles='[H]')],
-                                   p_species=[ARCSpecies(label='NH2', smiles='[NH2]'), ARCSpecies(label='H2', smiles='[H][H]')])
-
-        r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction_1, arc_reaction=arc_reaction)
-        self.assertEqual(r_map, {0: [0], 1: [1]})
-        self.assertEqual(p_map, {0: [0], 1: [1]})
-
-        r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction_2, arc_reaction=arc_reaction)
-        self.assertEqual(r_map, {0: [1], 1: [0]})
-        self.assertEqual(p_map, {0: [1], 1: [0]})
-
-        r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction_3, arc_reaction=arc_reaction)
-        self.assertEqual(r_map, {0: [0], 1: [1]})
-        self.assertEqual(p_map, {0: [1], 1: [0]})
-        rmg_reaction = Reaction(reactants=[Species(smiles='[CH3]'), Species(smiles='[CH3]')],
-                                products=[Species(smiles='CC')])
-        arc_reaction = ARCReaction(r_species=[ARCSpecies(label='CH3', smiles='[CH3]'),
-                                              ARCSpecies(label='CH3', smiles='[CH3]')],
-                                   p_species=[ARCSpecies(label='C2H6', smiles='CC')])
-
-        r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction, arc_reaction=arc_reaction)
-        self.assertEqual(r_map, {0: [0, 1], 1: [0, 1]})
-        self.assertEqual(p_map, {0: [0]})
-
-        rmg_reaction = Reaction(reactants=[Species(smiles='c1ccccc1CCC=C'), Species(smiles='CCO[O]')],
-                                products=[Species(smiles='c1ccccc1[CH]CC=C'), Species(smiles='CCOO')])
-        arc_reaction = ARCReaction(r_species=[ARCSpecies(label='butenylbenzene', smiles='c1ccccc1CCC=C'),
-                                              ARCSpecies(label='peroxyl', smiles='CCO[O]')],
-                                   p_species=[ARCSpecies(label='peroxide', smiles='CCOO'),
-                                              ARCSpecies(label='butenylbenzene_rad', smiles='c1ccccc1[CH]CC=C')])
-        r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction,
-                                                   arc_reaction=arc_reaction,
-                                                   concatenate=False,
-                                                   )
-        self.assertEqual(r_map, {0: 0, 1: 1})
-        self.assertEqual(p_map, {0: 1, 1: 0})
-
-        rmg_reaction = Reaction(reactants=[Species(smiles='[N]N'), Species(smiles='NN')],
-                                products=[Species(smiles='[NH]N'), Species(smiles='[NH]N')])
-        arc_reaction = ARCReaction(r_species=[ARCSpecies(label='H2NN(T)', smiles='[N]N'),
-                                              ARCSpecies(label='N2H4', smiles='NN')],
-                                   p_species=[ARCSpecies(label='N2H3', smiles='[NH]N'),
-                                              ARCSpecies(label='N2H3', smiles='[NH]N')])
-        r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction,
-                                           arc_reaction=arc_reaction,
-                                           concatenate=False,
-                                           )
-        self.assertEqual(r_map, {0: 0, 1: 1})
-        self.assertEqual(p_map, {0: 0, 1: 1})
-
+    # def test_get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(self):
+    #     """Test the get_atom_indices_of_labeled_atoms_in_an_rmg_reaction() function."""
+    #     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.arc_reaction_1)
+    #     r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.arc_reaction_1,
+    #                                                                           rmg_reaction=rmg_reactions[0])
+    #     self.assertEqual(r_dict['*1'], 0)
+    #     self.assertIn(r_dict['*2'], [1, 2, 3, 4])
+    #     self.assertEqual(r_dict['*3'], 5)
+    #     self.assertEqual(p_dict['*1'], 0)
+    #     self.assertIn(p_dict['*2'], [5, 6])
+    #     self.assertEqual(p_dict['*3'], 4)
+    #     self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.arc_reaction_1, rmg_reactions))
+    #
+    #     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.arc_reaction_2)
+    #     r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.arc_reaction_2,
+    #                                                                           rmg_reaction=rmg_reactions[0])
+    #     self.assertIn(r_dict['*1'], [0, 2])
+    #     self.assertIn(r_dict['*2'], [3, 4, 5, 8, 9, 10])
+    #     self.assertEqual(r_dict['*3'], 11)
+    #     self.assertEqual(p_dict['*1'], 0)
+    #     self.assertIn(p_dict['*2'], [11, 12, 13])
+    #     self.assertEqual(p_dict['*3'], 10)
+    #     self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.arc_reaction_2, rmg_reactions))
+    #
+    #     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.arc_reaction_4)
+    #     r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.arc_reaction_4,
+    #                                                                           rmg_reaction=rmg_reactions[0])
+    #     self.assertEqual(r_dict['*1'], 0)
+    #     self.assertEqual(r_dict['*2'], 2)
+    #     self.assertIn(r_dict['*3'], [7, 8])
+    #     self.assertEqual(p_dict['*1'], 0)
+    #     self.assertEqual(p_dict['*2'], 2)
+    #     self.assertIn(p_dict['*3'], [3, 4, 5])
+    #     self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.arc_reaction_4, rmg_reactions))
+    #
+    #     for atom, symbol in zip(self.rxn_2a.r_species[0].mol.atoms, ['C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H']):
+    #         self.assertEqual(atom.symbol, symbol)
+    #     self.assertEqual(self.rxn_2a.r_species[0].mol.atoms[0].radical_electrons, 0)
+    #     self.assertEqual(self.rxn_2a.r_species[0].mol.atoms[1].radical_electrons, 1)
+    #     self.assertEqual(self.rxn_2a.r_species[0].mol.atoms[2].radical_electrons, 0)
+    #     self.assertEqual(self.rxn_2a.p_species[0].mol.atoms[0].radical_electrons, 0)
+    #     self.assertEqual(self.rxn_2a.p_species[0].mol.atoms[1].radical_electrons, 0)
+    #     self.assertEqual(self.rxn_2a.p_species[0].mol.atoms[2].radical_electrons, 1)
+    #     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.rxn_2a)
+    #     r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.rxn_2a,
+    #                                                                           rmg_reaction=rmg_reactions[0])
+    #     self.assertEqual(r_dict['*1'], 1)
+    #     self.assertIn(r_dict['*2'], [0, 2])
+    #     self.assertIn(r_dict['*3'], [4, 5, 6, 7, 8, 9])
+    #     self.assertEqual(p_dict['*1'], 1)
+    #     self.assertEqual(p_dict['*2'], 2)
+    #     self.assertIn(p_dict['*3'], [3, 6])
+    #     self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.rxn_2a, rmg_reactions))
+    #
+    #     for atom, symbol in zip(self.rxn_2b.r_species[0].mol.atoms, ['C', 'C', 'H', 'H', 'H', 'H', 'C', 'H', 'H', 'H']):
+    #         self.assertEqual(atom.symbol, symbol)
+    #     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=self.rxn_2b)
+    #     r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=self.rxn_2b,
+    #                                                                           rmg_reaction=rmg_reactions[0])
+    #     self.assertEqual(r_dict['*1'], 1)
+    #     self.assertIn(r_dict['*2'], [0, 6])
+    #     self.assertIn(r_dict['*3'], [3, 4, 5, 7, 8, 9])
+    #     self.assertEqual(p_dict['*1'], 1)
+    #     self.assertEqual(p_dict['*2'], 2)
+    #     self.assertIn(p_dict['*3'], [3, 6])
+    #     self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(self.rxn_2b, rmg_reactions))
+    #
+    #     # C3H6O + C4H9O <=> C3H5O + C4H10O
+    #     r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O')
+    #     r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO')
+    #     p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O')
+    #     p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO')
+    #     rxn_1 = ARCReaction(reactants=['C3H6O', 'C4H9O'], products=['C3H5O', 'C4H10O'],
+    #                         r_species=[r_1, r_2], p_species=[p_1, p_2])
+    #     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn_1)
+    #     for rmg_reaction in rmg_reactions:
+    #         r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn_1,
+    #                                                                               rmg_reaction=rmg_reaction)
+    #         for d in [r_dict, p_dict]:
+    #             self.assertEqual(len(list(d.keys())), 3)
+    #             keys = list(d.keys())
+    #             for label in ['*1', '*2', '*3']:
+    #                 self.assertIn(label, keys)
+    #     self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(rxn_1, rmg_reactions))
+    #
+    #     p_1 = ARCSpecies(label='C3H5O', smiles='CC=C[O]')  # Use a wrong resonance structure and repeat the above.
+    #     rxn_2 = ARCReaction(reactants=['C3H6O', 'C4H9O'], products=['C3H5O', 'C4H10O'],
+    #                         r_species=[r_1, r_2], p_species=[p_1, p_2])
+    #     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn_2)
+    #     for rmg_reaction in rmg_reactions:
+    #         r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn_2,
+    #                                                                               rmg_reaction=rmg_reaction)
+    #         for d in [r_dict, p_dict]:
+    #             self.assertEqual(len(list(d.keys())), 3)
+    #             keys = list(d.keys())
+    #             for label in ['*1', '*2', '*3']:
+    #                 self.assertIn(label, keys)
+    #     self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(rxn_2, rmg_reactions))
+    #
+    #     # C3H6O + C4H9O <=> C3H5O + C4H10O
+    #     r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O', xyz=self.c3h6o_xyz)
+    #     r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO', xyz=self.c4h9o_xyz)
+    #     p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=self.c3h5o_xyz)
+    #     p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=self.c4h10o_xyz)
+    #     rxn_3 = ARCReaction(reactants=['C3H6O', 'C4H9O'], products=['C3H5O', 'C4H10O'],
+    #                         r_species=[r_1, r_2], p_species=[p_1, p_2])
+    #     rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn_3)
+    #     r_dict, p_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn_3,
+    #                                                                           rmg_reaction=rmg_reactions[0])
+    #     self.assertEqual(r_dict, {'*3': 10, '*1': 1, '*2': 7})
+    #     self.assertEqual(p_dict, {'*1': 1, '*3': 9, '*2': 16})
+    #     self.assertTrue(_check_r_n_p_symbols_between_rmg_and_arc_rxns(rxn_3, rmg_reactions))
+    #
+    # def test_map_arc_rmg_species(self):
+    #     """Test the map_arc_rmg_species() function."""
+    #     r_map, p_map = map_arc_rmg_species(
+    #         arc_reaction=ARCReaction(r_species=[ARCSpecies(label='CCjC', smiles='C[CH]C')],
+    #                                  p_species=[ARCSpecies(label='CjCC', smiles='[CH2]CC')]),
+    #         rmg_reaction=Reaction(reactants=[Species(smiles='C[CH]C')],
+    #                               products=[Species(smiles='[CH2]CC')]),
+    #         concatenate=False)
+    #     self.assertEqual(r_map, {0: 0})
+    #     self.assertEqual(p_map, {0: 0})
+    #
+    #     r_map, p_map = map_arc_rmg_species(
+    #         arc_reaction=ARCReaction(r_species=[ARCSpecies(label='CCjC', smiles='C[CH]C')],
+    #                                  p_species=[ARCSpecies(label='CjCC', smiles='[CH2]CC')]),
+    #         rmg_reaction=Reaction(reactants=[Species(smiles='C[CH]C')],
+    #                               products=[Species(smiles='[CH2]CC')]))
+    #     self.assertEqual(r_map, {0: [0]})
+    #     self.assertEqual(p_map, {0: [0]})
+    #
+    #     r_map, p_map = map_arc_rmg_species(arc_reaction=self.arc_reaction_1, rmg_reaction=self.rmg_reaction_1)
+    #     self.assertEqual(r_map, {0: [0], 1: [1]})
+    #     self.assertEqual(p_map, {0: [0], 1: [1]})
+    #
+    #     r_map, p_map = map_arc_rmg_species(arc_reaction=self.arc_reaction_1, rmg_reaction=self.rmg_reaction_2)
+    #     self.assertEqual(r_map, {0: [1], 1: [0]})
+    #     self.assertEqual(p_map, {0: [0], 1: [1]})
+    #
+    #     r_map, p_map = map_arc_rmg_species(arc_reaction=self.arc_reaction_3, rmg_reaction=self.rmg_reaction_3)
+    #     self.assertEqual(r_map, {0: [0, 1], 1: [0, 1]})
+    #     self.assertEqual(p_map, {0: [0]})
+    #
+    #     rmg_reaction_1 = Reaction(reactants=[Species(smiles='N'), Species(smiles='[H]')],
+    #                               products=[Species(smiles='[NH2]'), Species(smiles='[H][H]')])
+    #     rmg_reaction_2 = Reaction(reactants=[Species(smiles='[H]'), Species(smiles='N')],
+    #                               products=[Species(smiles='[H][H]'), Species(smiles='[NH2]')])
+    #     rmg_reaction_3 = Reaction(reactants=[Species(smiles='N'), Species(smiles='[H]')],
+    #                               products=[Species(smiles='[H][H]'), Species(smiles='[NH2]')])
+    #     arc_reaction = ARCReaction(r_species=[ARCSpecies(label='NH3', smiles='N'), ARCSpecies(label='H', smiles='[H]')],
+    #                                p_species=[ARCSpecies(label='NH2', smiles='[NH2]'), ARCSpecies(label='H2', smiles='[H][H]')])
+    #
+    #     r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction_1, arc_reaction=arc_reaction)
+    #     self.assertEqual(r_map, {0: [0], 1: [1]})
+    #     self.assertEqual(p_map, {0: [0], 1: [1]})
+    #
+    #     r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction_2, arc_reaction=arc_reaction)
+    #     self.assertEqual(r_map, {0: [1], 1: [0]})
+    #     self.assertEqual(p_map, {0: [1], 1: [0]})
+    #
+    #     r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction_3, arc_reaction=arc_reaction)
+    #     self.assertEqual(r_map, {0: [0], 1: [1]})
+    #     self.assertEqual(p_map, {0: [1], 1: [0]})
+    #     rmg_reaction = Reaction(reactants=[Species(smiles='[CH3]'), Species(smiles='[CH3]')],
+    #                             products=[Species(smiles='CC')])
+    #     arc_reaction = ARCReaction(r_species=[ARCSpecies(label='CH3', smiles='[CH3]'),
+    #                                           ARCSpecies(label='CH3', smiles='[CH3]')],
+    #                                p_species=[ARCSpecies(label='C2H6', smiles='CC')])
+    #
+    #     r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction, arc_reaction=arc_reaction)
+    #     self.assertEqual(r_map, {0: [0, 1], 1: [0, 1]})
+    #     self.assertEqual(p_map, {0: [0]})
+    #
+    #     rmg_reaction = Reaction(reactants=[Species(smiles='c1ccccc1CCC=C'), Species(smiles='CCO[O]')],
+    #                             products=[Species(smiles='c1ccccc1[CH]CC=C'), Species(smiles='CCOO')])
+    #     arc_reaction = ARCReaction(r_species=[ARCSpecies(label='butenylbenzene', smiles='c1ccccc1CCC=C'),
+    #                                           ARCSpecies(label='peroxyl', smiles='CCO[O]')],
+    #                                p_species=[ARCSpecies(label='peroxide', smiles='CCOO'),
+    #                                           ARCSpecies(label='butenylbenzene_rad', smiles='c1ccccc1[CH]CC=C')])
+    #     r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction,
+    #                                                arc_reaction=arc_reaction,
+    #                                                concatenate=False,
+    #                                                )
+    #     self.assertEqual(r_map, {0: 0, 1: 1})
+    #     self.assertEqual(p_map, {0: 1, 1: 0})
+    #
+    #     rmg_reaction = Reaction(reactants=[Species(smiles='[N]N'), Species(smiles='NN')],
+    #                             products=[Species(smiles='[NH]N'), Species(smiles='[NH]N')])
+    #     arc_reaction = ARCReaction(r_species=[ARCSpecies(label='H2NN(T)', smiles='[N]N'),
+    #                                           ARCSpecies(label='N2H4', smiles='NN')],
+    #                                p_species=[ARCSpecies(label='N2H3', smiles='[NH]N'),
+    #                                           ARCSpecies(label='N2H3', smiles='[NH]N')])
+    #     r_map, p_map = map_arc_rmg_species(rmg_reaction=rmg_reaction,
+    #                                        arc_reaction=arc_reaction,
+    #                                        concatenate=False,
+    #                                        )
+    #     self.assertEqual(r_map, {0: 0, 1: 1})
+    #     self.assertEqual(p_map, {0: 0, 1: 1})
 
     def test_find_equivalent_atoms_in_reactants_and_products(self):
         """Test the find_equivalent_atoms_in_reactants_and_products() function"""
@@ -1141,7 +1075,6 @@ def test_check_species_before_mapping(self):
                                                      verbose=True))
         self.assertTrue(check_species_before_mapping(spc_1=self.spc1, spc_2=self.spc2, verbose=True))
 
-
     def test_get_bonds_dict(self):
         """Test the get_bonds_dict function."""
         bond_dict = get_bonds_dict(spc=ARCSpecies(label='CH4', smiles='C'))
@@ -1387,22 +1320,20 @@ def test_make_bond_changes(self):
         label_species_atoms([spc1])
         label_species_atoms([spc2])
         rxn = ARCReaction(r_species = [spc1], p_species=[spc2])
-        rxn.determine_family(self.db)
         r_label_dict = {'*1': 0, '*2': 1}
         l = [spc1]
         make_bond_changes(rxn, l, r_label_dict)
         self.assertTrue(spc2.mol.is_isomorphic(l[0].mol))
-        rxn = ARCReaction(r_species = [ARCSpecies(label="N4", smiles = "NNNN")],
-                          p_species = [ARCSpecies(label="NH3", smiles = "N"),
-                                       ARCSpecies(label="NH2NHN_p", smiles = "[N-]=[NH+]N")])
-        rxn.determine_family(self.db)
-        rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn, backend="arc")
-        r_label_dict, p_label_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn,
-                                                                                        rmg_reaction=rmg_reactions[0])
-        assign_labels_to_products(rxn, p_label_dict)
+        rxn = ARCReaction(r_species=[ARCSpecies(label="N4", smiles="NNNN")],
+                          p_species=[ARCSpecies(label="NH3", smiles="N"),
+                                     ARCSpecies(label="NH2NHN_p", smiles="[N-]=[NH+]N")])
+        # rmg_reactions = get_rmg_reactions_from_arc_reaction(arc_reaction=rxn, backend="arc")
+        # r_label_dict, p_label_dict = get_atom_indices_of_labeled_atoms_in_an_rmg_reaction(arc_reaction=rxn,
+        #                                                                                 rmg_reaction=rmg_reactions[0])
+        assign_labels_to_products(rxn)
         reactants, products = copy_species_list_for_mapping(rxn.r_species), copy_species_list_for_mapping(rxn.p_species)
         label_species_atoms(reactants), label_species_atoms(products)
-        r_bdes, _ = find_all_bdes(rxn, r_label_dict, True), find_all_bdes(rxn, p_label_dict, False)
+        r_bdes, _ = find_all_bdes(rxn, True), find_all_bdes(rxn, False)
         r_cuts = cut_species_based_on_atom_indices(reactants, r_bdes)
         self.assertFalse(r_cuts[1].mol.is_isomorphic(rxn.p_species[1].mol))
         make_bond_changes(rxn=rxn,
@@ -1412,15 +1343,15 @@ def test_make_bond_changes(self):
 
     def test_update_xyz(self):
         """tests the update_xyz function"""
-        spc = ARCSpecies(label="test_UX",smiles = "BrC(F)Cl")
+        spc = ARCSpecies(label="test_UX", smiles="BrC(F)Cl")
         shuffle(spc.mol.atoms)
         update_xyz([spc])
         xyz = spc.get_xyz()["symbols"]
         atoms = [atom.element.symbol for atom in spc.mol.atoms]
         for label1, label2 in zip(atoms, xyz):
             self.assertEqual(label1, label2)
-        
-        spc = ARCSpecies(label="test_UX", smiles = "OCl")
+
+        spc = ARCSpecies(label="test_UX", smiles="OCl")
         shuffle(spc.mol.atoms)
         update_xyz([spc])
         xyz = spc.get_xyz()["symbols"]
@@ -1428,36 +1359,36 @@ def test_update_xyz(self):
         for label1, label2 in zip(atoms, xyz):
             self.assertEqual(label1, label2)
 
-        spc = ARCSpecies(label="test_UX", smiles = "BrOCl")
+        spc = ARCSpecies(label="test_UX", smiles="BrOCl")
         shuffle(spc.mol.atoms)
         update_xyz([spc])
         xyz = spc.get_xyz()["symbols"]
         atoms = [atom.element.symbol for atom in spc.mol.atoms]
-        for label1,label2 in zip(atoms, xyz):
+        for label1, label2 in zip(atoms, xyz):
             self.assertEqual(label1, label2)
 
     def test_add_adjacent_hydrogen_atoms_to_map_based_on_a_specific_torsion(self):
         "test the add_adjacent_hydrogen_atoms_to_map_based_on_a_specific_torsion function"
-        spc1 = ARCSpecies(label="c4", smiles = "CCCC")
+        spc1 = ARCSpecies(label="c4", smiles="CCCC")
         spc2 = spc1.copy()
         out_dict = add_adjacent_hydrogen_atoms_to_map_based_on_a_specific_torsion(spc1,
                                                                                   spc2,
                                                                                   spc1.mol.atoms[0],
                                                                                   spc2.mol.atoms[0],
-                                                                                  [0,1,2,3],
-                                                                                  {0: 0,1: 1,2: 2,3: 3},
+                                                                                  [0, 1, 2, 3],
+                                                                                  {0: 0, 1: 1, 2: 2, 3: 3},
                                                                                   True)
         for key in range(7):
             self.assertEqual(out_dict[key], key)
-    
-        spc1 = ARCSpecies(label="c4", smiles = "cccc")
+
+        spc1 = ARCSpecies(label="c4", smiles="cccc")
         spc2 = spc1.copy()
         out_dict = add_adjacent_hydrogen_atoms_to_map_based_on_a_specific_torsion(spc1,
                                                                                   spc2,
                                                                                   spc1.mol.atoms[0],
                                                                                   spc2.mol.atoms[0],
-                                                                                  [0,1,2,3],
-                                                                                  {0: 0,1: 1,2: 2,3: 3},
+                                                                                  [0, 1, 2, 3],
+                                                                                  {0: 0, 1: 1, 2: 2, 3: 3},
                                                                                   True)
         for key in range(4):
             self.assertEqual(out_dict[key], key)
@@ -1468,8 +1399,8 @@ def test_add_adjacent_hydrogen_atoms_to_map_based_on_a_specific_torsion(self):
                                                                                   spc2,
                                                                                   spc1.mol.atoms[0],
                                                                                   spc2.mol.atoms[0],
-                                                                                  [0,1,2,3],
-                                                                                  {0: 0,1: 1,2: 2,3: 3},
+                                                                                  [0, 1, 2, 3],
+                                                                                  {0: 0, 1: 1, 2: 2, 3: 3},
                                                                                   True)
         for key in range(4):
             self.assertEqual(out_dict[key], key)
@@ -1477,9 +1408,8 @@ def test_add_adjacent_hydrogen_atoms_to_map_based_on_a_specific_torsion(self):
     def test_find_all_bdes(self):
         """tests the find_all_bdes function"""
         rxn = ARCReaction(r_species=[self.r_1, self.r_2], p_species=[self.p_1, self.p_2])
-        rxn.determine_family(self.db)
-        bdes = find_all_bdes(rxn, self.r_label_dict_rxn_1, True)
-        self.assertEqual(bdes, [(2, 4)])
+        bdes = find_all_bdes(rxn, True)
+        self.assertEqual(bdes, [(4, 6)])
 
     def test_copy_species_list_for_mapping(self):
         """tests the copy_species_list_for_mapping function"""
@@ -1500,5 +1430,6 @@ def test_determine_bdes_on_spc_based_on_atom_labels(self):
         self.assertTrue(determine_bdes_on_spc_based_on_atom_labels(spc, (1, 2)))
         self.assertFalse(determine_bdes_on_spc_based_on_atom_labels(spc, (2, 3)))
 
+
 if __name__ == '__main__':
     unittest.main(testRunner=unittest.TextTestRunner(verbosity=2))
\ No newline at end of file
diff --git a/arc/reaction/__init__.py b/arc/reaction/__init__.py
new file mode 100644
index 0000000000..e33a984d39
--- /dev/null
+++ b/arc/reaction/__init__.py
@@ -0,0 +1,2 @@
+import arc.reaction.family
+from arc.reaction.reaction import ARCReaction
diff --git a/arc/reaction/family.py b/arc/reaction/family.py
new file mode 100644
index 0000000000..090586bdb0
--- /dev/null
+++ b/arc/reaction/family.py
@@ -0,0 +1,827 @@
+"""
+A module for working with RMG reaction families.
+"""
+
+from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union
+import ast
+import os
+import re
+
+from rmgpy.molecule import Bond, Group, Molecule
+
+from arc.common import clean_text, generate_resonance_structures, get_logger
+from arc.imports import settings
+
+if TYPE_CHECKING:
+    from arc.species import ARCSpecies
+    from arc.reaction.reaction import ARCReaction
+
+RMG_DB_PATH = settings['RMG_DB_PATH']
+ARC_FAMILIES_PATH = settings['ARC_FAMILIES_PATH']
+
+
+logger = get_logger()
+
+
+class ReactionFamily(object):
+    """
+    A class for representing a reaction family.
+
+    Args:
+        label (str): The reaction family label.
+        consider_arc_families (bool, optional): Whether to consider ARC's custom families
+                                                 when searching for the family groups file.
+
+    Attributes:
+        label (str): The reaction family label.
+    """
+
+    def __init__(self,
+                 label: str,
+                 consider_arc_families: bool = True,
+                 ):
+        if label is None:
+            raise ValueError('Cannot initialize a ReactionFamily object without a label')
+        self.label = label
+        self.groups_as_lines = self.get_groups_file_as_lines(consider_arc_families=consider_arc_families)
+        self.reversible = is_reversible(self.groups_as_lines)
+        self.own_reverse = is_own_reverse(self.groups_as_lines)
+        self.reactants = get_reactant_groups_from_template(self.groups_as_lines)
+        self.reactant_num = self.get_reactant_num()
+        self.product_num = get_product_num(self.groups_as_lines)
+        entry_labels = list()
+        for reactant_group in self.reactants:
+            entry_labels.extend(reactant_group)
+        self.entries = get_entries(self.groups_as_lines, entry_labels=entry_labels)
+        self.actions = get_recipe_actions(self.groups_as_lines)
+
+    def __str__(self):
+        """
+        A string representation of the object.
+        """
+        return f'ReactionFamily(label={self.label})'
+
+    def get_groups_file_as_lines(self, consider_arc_families: bool = True) -> List[str]:
+        """
+        Get the groups file as a list of lines.
+        Precedence is given to RMG families (ARC families should therefore have distinct names than RMG's)
+
+        Args:
+            consider_arc_families (bool, optional): Whether to consider ARC's custom families.
+
+        Returns:
+            List[str]: The groups file as a list of lines.
+        """
+        groups_path = os.path.join(RMG_DB_PATH, 'input', 'kinetics', 'families', self.label, 'groups.py')
+           print(f"Looking for groups.py in RMG database at: {groups_path}")  # Debug statement
+            if consider_arc_families:
+                groups_path = os.path.join(ARC_FAMILIES_PATH, f'{self.label}.py')
+            if not os.path.isfile(groups_path):
+                raise FileNotFoundError(f'Could not find the groups file for family {self.label}')
+        with open(groups_path, 'r') as f:
+            groups_as_lines = f.readlines()
+        return groups_as_lines
+
+    def generate_products(self,
+                          reactants: List['ARCSpecies'],
+                          ) -> Dict[Union[str, Tuple[str, str]], List[Tuple[List['Molecule'], Dict[int, str]]]]:
+        """
+        Generate a list of all the possible reaction products of this family starting from the list of ``reactants``.
+
+        reactant_to_group_maps has the following structure::
+
+            {0: [{'group': 1, 'subgroup': <label of group that is subgraphisomorphic with reactant 0>}, ...],
+             1: [{'group': 0, 'subgroup': <label of group that is subgraphisomorphic with reactant 1>}, ...]}
+
+        Args:
+            reactants (List['ARCSpecies']): The reactants to generate reaction products for.
+
+        Returns:
+            Dict[Union[str, Tuple[str, str]], List[Tuple[List['Molecule'], Dict[int, str]]]]:
+                The generated reaction products in different possible reaction paths including iso-teleological paths.
+                keys are family group labels used to generate the products,
+                values are a list of the corresponding possible products and isomorphic subgraphs.
+        """
+        if self.reactant_num != len(reactants):
+            return dict()
+        reactant_to_group_maps = dict()
+        for reactant_idx, reactant in enumerate(reactants):
+            for groups_idx, group_labels in enumerate(self.reactants):
+                for group_label in group_labels:
+                    group = Group().from_adjacency_list(
+                        get_group_adjlist(self.groups_as_lines, entry_label=group_label))
+                    for mol in reactant.mol_list or [reactant.mol]:
+                        splits = group.split()
+                        if mol.is_subgraph_isomorphic(other=group, save_order=True) \
+                                or len(splits) > 1 and any(mol.is_subgraph_isomorphic(other=g, save_order=True) for g in splits):
+                            if reactant_idx not in reactant_to_group_maps:
+                                reactant_to_group_maps[reactant_idx] = list()
+                            reactant_to_group_maps[reactant_idx].append({'group': groups_idx, 'subgroup': group_label})
+        if self.reactant_num != len(reactant_to_group_maps.keys()):
+            return dict()
+        return self.generate_products_by_reactant_groups(reactants=reactants,
+                                                         reactant_to_group_maps=reactant_to_group_maps)
+
+    def generate_products_by_reactant_groups(self,
+                                             reactants: List['ARCSpecies'],
+                                             reactant_to_group_maps: Dict[int, List[Dict[str, Union[int, str]]]],
+                                             ) -> Dict[Union[str, Tuple[str, str]], List[Tuple[List['Molecule'], Dict[int, str]]]]:
+        """
+        Generate a list of all the possible reaction products of this family starting from the list of ``reactants``
+        and the mapping of reactant indices to family groups.
+
+        Args:
+            reactants (List['ARCSpecies']): The reactants to generate reaction products for.
+            reactant_to_group_maps (Dict[int, List[Dict[str, Union[int, str]]]]): A dictionary mapping reactant indices
+                                                                                  to groups that match them.
+
+        Returns:
+            Dict[str, List[Tuple[List['Molecule'], Dict[int, str]]]]:
+                The generated reaction products.
+                Keys are family group labels used to generate the products.
+                Values are lists of tuples with entries:
+                (0) a list of the corresponding possible reactions, (1) the isomorphic subgraph.
+        """
+        if len(reactants) == 1:
+            return self.generate_unimolecular_products(reactants=reactants,
+                                                       reactant_to_group_maps=reactant_to_group_maps)
+        elif len(reactants) == 2:
+            return self.generate_bimolecular_products(reactants=reactants,
+                                                      reactant_to_group_maps=reactant_to_group_maps)
+        logger.error(f'Unsupported number of reactants encountered in generate_products_by_reactant_groups: '
+                     f'{len(reactants)}')
+        return dict()
+
+    def generate_unimolecular_products(self,
+                                       reactants: List['ARCSpecies'],
+                                       reactant_to_group_maps: Dict[int, List[Dict[str, Union[int, str]]]],
+                                       ) -> Dict[str, List[Tuple[List['Molecule'], Dict[int, str]]]]:
+        """
+        Generate a list of all the possible unimolecular reaction products of this family starting from
+        the list of ``reactants`` and the mapping of reactant indices to family groups.
+
+        Args:
+            reactants (List['ARCSpecies']): The reactants to generate reaction products for.
+            reactant_to_group_maps (Dict[int, List[Dict[str, Union[int, str]]]]): A dictionary mapping reactant indices
+                                                                                  to groups that match them.
+
+        Returns:
+            Dict[str, List[Tuple[List['Molecule'], Dict[int, str]]]]:
+                The generated reaction products.
+                Keys are family group labels used to generate the products.
+                Values are lists of tuples with entries:
+                (0) a list of the corresponding possible reactions, (1) the isomorphic subgraph.
+        """
+        isomorphic_subgraph_dicts = list()
+        reactant_to_group_maps = reactant_to_group_maps[0]
+        for mol in reactants[0].mol_list or [reactants[0].mol]:
+            for reactant_to_group_map in reactant_to_group_maps:
+                group = Group().from_adjacency_list(get_group_adjlist(self.groups_as_lines,
+                                                                      entry_label=reactant_to_group_map['subgroup']))
+                isomorphic_subgraphs = mol.find_subgraph_isomorphisms(other=group, save_order=True)
+                if len(isomorphic_subgraphs):
+                    for isomorphic_subgraph in isomorphic_subgraphs:
+                        isomorphic_subgraph_dicts.append(
+                            {'mols': [mol],
+                             'groups': [group],
+                             'subgroup': reactant_to_group_map['subgroup'],
+                             'isomorphic_subgraph': {mol.atoms.index(atom): group_atom.label
+                                                     for atom, group_atom in isomorphic_subgraph.items()}})
+        products_by_group = dict()
+        for isomorphic_subgraph_dict in isomorphic_subgraph_dicts:
+            try:
+                product_list = self.apply_recipe(mols=isomorphic_subgraph_dict['mols'],
+                                                 isomorphic_subgraph=isomorphic_subgraph_dict['isomorphic_subgraph'])
+            except ValueError:
+                continue
+            if product_list is not None:
+                if isomorphic_subgraph_dict['subgroup'] not in products_by_group:
+                    products_by_group[isomorphic_subgraph_dict['subgroup']] = list()
+                products_by_group[isomorphic_subgraph_dict['subgroup']].append((product_list,
+                                                                                isomorphic_subgraph_dict['isomorphic_subgraph']))
+        return products_by_group
+
+    def generate_bimolecular_products(self,
+                                      reactants: List['ARCSpecies'],
+                                      reactant_to_group_maps: Dict[int, List[Dict[str, Union[int, str]]]],
+                                      ) -> Dict[Tuple[str, str], List[Tuple[List['Molecule'], Dict[int, str]]]]:
+        """
+        Generate a list of all the possible bimolecular reaction products of this family starting from
+        the list of ``reactants`` and the mapping of reactant indices to family groups.
+
+        reactant_to_group_maps has the following structure::
+
+            {0: [{'group': 1, 'subgroup': <label of group that is subgraphisomorphic with reactant 0>}, ...],
+             1: [{'group': 0, 'subgroup': <label of group that is subgraphisomorphic with reactant 1>}, ...]}
+
+        Args:
+            reactants (List['ARCSpecies']): The reactants to generate reaction products for.
+            reactant_to_group_maps (Dict[int, List[Dict[str, Union[int, str]]]]): A dictionary mapping reactant indices
+                                                                                  to groups that match them.
+
+        Returns:
+            Dict[Tuple[str, str], List[Tuple[List['Molecule'], Dict[int, str]]]]:
+                The generated reaction products.
+                Keys are family group labels used to generate the products.
+                Values are lists of tuples with entries:
+                (0) a list of the corresponding possible reactions, (1) the isomorphic subgraph.
+        """
+        if list(reactant_to_group_maps.keys()) != [0, 1]:
+            return dict()
+        isomorphic_subgraph_dicts = list()
+        for mol_1 in reactants[0].mol_list or [reactants[0].mol]:
+            for mol_2 in reactants[1].mol_list or [reactants[1].mol]:
+                splits = Group().from_adjacency_list(
+                    get_group_adjlist(self.groups_as_lines, entry_label=reactant_to_group_maps[0][0]['subgroup'])).split()
+                if len(splits) > 1:
+                    for i in [0, 1]:
+                        isomorphic_subgraphs_1 = mol_1.find_subgraph_isomorphisms(other=splits[i], save_order=True)
+                        isomorphic_subgraphs_2 = mol_2.find_subgraph_isomorphisms(other=splits[not i], save_order=True)
+                        if len(isomorphic_subgraphs_1) and len(isomorphic_subgraphs_2):
+                            for isomorphic_subgraph_1 in isomorphic_subgraphs_1:
+                                for isomorphic_subgraph_2 in isomorphic_subgraphs_2:
+                                    isomorphic_subgraph_dicts.append(
+                                        {'mols': [mol_1, mol_2],
+                                         'subgroups': reactant_to_group_maps[0][0]['subgroup'],
+                                         'isomorphic_subgraph': get_isomorphic_subgraph(isomorphic_subgraph_1,
+                                                                                        isomorphic_subgraph_2,
+                                                                                        mol_1,
+                                                                                        mol_2)})
+                    continue
+                for reactant_to_group_map_1 in reactant_to_group_maps[0]:
+                    group_1 = Group().from_adjacency_list(get_group_adjlist(self.groups_as_lines,
+                                                                            entry_label=reactant_to_group_map_1['subgroup']))
+                    for reactant_to_group_map_2 in reactant_to_group_maps[1]:
+                        group_2 = Group().from_adjacency_list(get_group_adjlist(self.groups_as_lines,
+                                                                                entry_label=reactant_to_group_map_2['subgroup']))
+                        isomorphic_subgraphs_1 = mol_1.find_subgraph_isomorphisms(other=group_1, save_order=True)
+                        isomorphic_subgraphs_2 = mol_2.find_subgraph_isomorphisms(other=group_2, save_order=True)
+                        if len(isomorphic_subgraphs_1) and len(isomorphic_subgraphs_2):
+                            for isomorphic_subgraph_1 in isomorphic_subgraphs_1:
+                                for isomorphic_subgraph_2 in isomorphic_subgraphs_2:
+                                    isomorphic_subgraph_dicts.append(
+                                        {'mols': [mol_1, mol_2],
+                                         'subgroups': (reactant_to_group_map_1['subgroup'],
+                                                       reactant_to_group_map_2['subgroup']),
+                                         'isomorphic_subgraph': get_isomorphic_subgraph(isomorphic_subgraph_1,
+                                                                                        isomorphic_subgraph_2,
+                                                                                        mol_1,
+                                                                                        mol_2)})
+        products_by_group = dict()
+        for isomorphic_subgraph_dict in isomorphic_subgraph_dicts:
+            try:
+                product_list = self.apply_recipe(mols=isomorphic_subgraph_dict['mols'],
+                                                 isomorphic_subgraph=isomorphic_subgraph_dict['isomorphic_subgraph'])
+            except ValueError:
+                continue
+            if product_list is not None:
+                if isomorphic_subgraph_dict['subgroups'] not in products_by_group:
+                    products_by_group[isomorphic_subgraph_dict['subgroups']] = list()
+                products_by_group[isomorphic_subgraph_dict['subgroups']].append((product_list,
+                                                                                isomorphic_subgraph_dict['isomorphic_subgraph']))
+        return products_by_group
+
+    def apply_recipe(self,
+                     mols: List['Molecule'],
+                     isomorphic_subgraph: Dict[int, str],
+                     ) -> Optional[List['Molecule']]:
+        """
+        Generate a reaction product of this family from a reactant mol and the isomorphic subgraph
+        using the family's recipe.
+
+        Args:
+            mols (['Molecule']): The reactant molecule(s).
+            isomorphic_subgraph (Dict[int, str]): A dictionary representing the isomorphic subgraph.
+
+        Raises:
+            ValueError: If an invalid action is encountered.
+
+        Returns:
+            Optional[List['Molecule']]: The generated reaction product(s).
+        """
+        structure = Molecule()
+        for mol in mols:
+            structure = structure.merge(mol.copy(deep=True))
+        structure = add_labels_to_molecule(structure, isomorphic_subgraph)
+        for action in self.actions:
+            if action[0] in ['CHANGE_BOND', 'FORM_BOND', 'BREAK_BOND']:
+                structure.reset_connectivity_values()
+                label_1, info, label_2 = action[1:]
+                atom_1 = structure.get_labeled_atoms(label_1)[0]
+                atom_2 = structure.get_labeled_atoms(label_2)[0]
+                if atom_1 is None or atom_2 is None or atom_1 is atom_2:
+                    raise ValueError('Invalid atom labels in reaction recipe.')
+                if action[0] == 'CHANGE_BOND':
+                    if not structure.has_bond(atom_1, atom_2):
+                        raise ValueError('Attempted to change a nonexistent bond.')
+                    bond = structure.get_bond(atom_1, atom_2)
+                    if bond.is_benzene():
+                        structure.props['validAromatic'] = False
+                    atom_1.apply_action(['CHANGE_BOND', label_1, info, label_2])
+                    atom_2.apply_action(['CHANGE_BOND', label_1, info, label_2])
+                    bond.apply_action(['CHANGE_BOND', label_1, info, label_2])
+                elif action[0] == 'FORM_BOND':
+                    if structure.has_bond(atom_1, atom_2):
+                        raise ValueError('Attempted to create an existing bond.')
+                    if info != 1:
+                        raise ValueError(f'Attempted to create bond of type {info}')
+                    bond = Bond(atom_1, atom_2, order=info)
+                    structure.add_bond(bond)
+                    atom_1.apply_action(['FORM_BOND', label_1, info, label_2])
+                    atom_2.apply_action(['FORM_BOND', label_1, info, label_2])
+                elif action[0] == 'BREAK_BOND':
+                    if not structure.has_bond(atom_1, atom_2):
+                        raise ValueError('Attempted to remove a nonexistent bond.')
+                    bond = structure.get_bond(atom_1, atom_2)
+                    structure.remove_bond(bond)
+                    atom_1.apply_action(['BREAK_BOND', label_1, info, label_2])
+                    atom_2.apply_action(['BREAK_BOND', label_1, info, label_2])
+            elif action[0] in ['LOSE_RADICAL', 'GAIN_RADICAL', 'LOSE_PAIR', 'GAIN_PAIR']:
+                label, change = action[1:]
+                change = int(change)
+                atom = structure.get_labeled_atoms(label)[0]
+                if atom is None:
+                    raise ValueError(f'Unable to find atom with label "{label}" while applying reaction recipe.')
+                atom.apply_action([action[0], label, change])
+            else:
+                raise ValueError(f'Unknown action "{action[0]}" encountered.')
+        if 'validAromatic' in structure.props and not structure.props['validAromatic']:
+            structure.kekulize()
+        structures = structure.split()
+        if self.product_num != len(structures):
+            return None
+        updated_structures = list()
+        for structure in structures:
+            structure.update(log_species=False, raise_atomtype_exception=False, sort_atoms=False)
+            updated_structures.append(structure)
+        return updated_structures
+
+    def get_reactant_num(self) -> int:
+        """
+        Get the number of reactants for this family.
+
+        Returns:
+            int: The number of reactants.
+        """
+        if len(self.reactants) == 1:
+            group = Group().from_adjacency_list(get_group_adjlist(self.groups_as_lines, entry_label=self.reactants[0][0]))
+            groups = group.split()
+            return len(groups)
+        else:
+            return len(self.reactants)
+
+
+def get_reaction_family_products(rxn: 'ARCReaction',
+                                 rmg_family_set: Optional[Union[List[str], str]] = None,
+                                 consider_rmg_families: bool = True,
+                                 consider_arc_families: bool = True,
+                                 discover_own_reverse_rxns_in_reverse: bool = False,
+                                 ) -> List[dict]:
+    """
+    Determine the RMG reaction family for a given ARC reaction by generating corresponding product dicts.
+
+    Args:
+        rxn ('ARCReaction'): The ARC reaction object.
+        rmg_family_set (Union[List[str], str], optional): The RMG family set to use from
+                                                          RMG-database/input/kinetics/families/recommended.py.
+                                                          Can be a name of a defined set, or a list
+                                                          of explicit family lables to consider.
+                                                          Note that surface families are excluded if 'all' is used.
+        consider_rmg_families (bool, optional): Whether to consider RMG's families.
+        consider_arc_families (bool, optional): Whether to consider ARC's custom families.
+        discover_own_reverse_rxns_in_reverse (bool, optional): Whether to discover reactions belonging to a family
+                                                               which is its own reverse (its template applied in
+                                                               reverse is the same) from both directions.
+                                                               ``True`` will cause the function to discover reactions
+                                                               in both directions, ``False`` will cause the function
+                                                               to discover reactions only in the forward direction.
+
+    Returns:
+        List[dict]: The list of product dictionaries with the reaction family label.
+                    Keys are: 'family', 'group_labels', 'products', 'own_reverse', 'discovered_in_reverse', 'actions'.
+    """
+    family_labels = get_all_families(rmg_family_set=rmg_family_set or rxn.rmg_family_set,
+                                     consider_rmg_families=consider_rmg_families,
+                                     consider_arc_families=consider_arc_families)
+    product_dicts = list()
+    for family_label in family_labels:
+        # Forward:
+        products = determine_possible_reaction_products_from_family(rxn=rxn,
+                                                                    family_label=family_label,
+                                                                    consider_arc_families=consider_arc_families,
+                                                                    reverse=False,
+                                                                    )
+        if len(products):
+            product_dicts.extend(filter_products_by_reaction(rxn=rxn, product_dicts=products))
+
+        # Reverse:
+        flipped_rxn = rxn.flip_reaction(report_family=False)
+        products = determine_possible_reaction_products_from_family(rxn=flipped_rxn,
+                                                                    family_label=family_label,
+                                                                    consider_arc_families=consider_arc_families,
+                                                                    reverse=True,
+                                                                    )
+        if len(products):
+            filtered_products = filter_products_by_reaction(rxn=flipped_rxn, product_dicts=products)
+            if not discover_own_reverse_rxns_in_reverse:
+                product_dicts.extend([prod for prod in filtered_products if not prod['own_reverse']])
+            else:
+                product_dicts.extend(filtered_products)
+    return product_dicts
+
+
+def determine_possible_reaction_products_from_family(rxn: 'ARCReaction',
+                                                     family_label: str,
+                                                     consider_arc_families: bool = True,
+                                                     reverse: bool = False,
+                                                     ) -> List[dict]:
+    """
+    Determine the possible reaction products for a given ARC reaction and a given RMG reaction family.
+
+    Args:
+        rxn ('ARCReaction'): The ARC reaction object.
+        family_label (str): The reaction family label.
+        consider_arc_families (bool, optional): Whether to consider ARC's custom families.
+        reverse (bool, optional): Whether the reaction is in reverse.
+
+    Returns:
+        List[dict]: A list of dictionaries, each containing the family label, the group labels, the products,
+                    and whether the family's template also represents its own reverse.
+    """
+    product_dicts = list()
+    family = ReactionFamily(label=family_label, consider_arc_families=consider_arc_families)
+    products = family.generate_products(reactants=rxn.get_reactants_and_products(arc=True, return_copies=True)[0])
+    if products:
+        for group_labels, product_lists in products.items():
+            for product_list in product_lists:
+                product_dicts.append({'family': family_label,
+                                      'group_labels': group_labels,
+                                      'products': product_list[0],
+                                      'label_map': {val: key for key, val in product_list[1].items() if val},
+                                      'own_reverse': family.own_reverse,
+                                      'discovered_in_reverse': reverse,
+                                      })
+    return product_dicts
+
+
+def filter_products_by_reaction(rxn: 'ARCReaction',
+                                product_dicts: List[dict],
+                                ) -> List[dict]:
+    """
+    Filter the possible reaction products by the ARC reaction.
+
+    Args:
+        rxn ('ARCReaction'): The ARC reaction object.
+        product_dicts (List[dict]): A list of dictionaries, each containing the family label, the group labels,
+                                    the products, and whether the family's template also represents its own reverse.
+
+    Returns:
+        List[dict]: The filtered list of product dictionaries.
+    """
+    filtered_product_dicts = list()
+    r_species, p_species = rxn.get_reactants_and_products(arc=True, return_copies=True)
+    for product_dict in product_dicts:
+        if len(product_dict['products']) != len(p_species):
+            continue
+        if check_product_isomorphism(product_dict['products'], p_species):
+            filtered_product_dicts.append(product_dict)
+    return filtered_product_dicts
+
+
+def check_product_isomorphism(products: List['Molecule'],
+                              p_species: List['ARCSpecies'],
+                              ) -> bool:
+    """
+    Check whether the products are isomorphic to the given species.
+    Supports unimolecular and bimolecular reactions.
+
+    Args:
+        products (Tuple[List['Molecule'], Dict[int, str]]): The products to check.
+        p_species (List['ARCSpecies']): The species to check against.
+
+    Returns:
+        bool: Whether the products are isomorphic to the species.
+    """
+    prods_a = [generate_resonance_structures(mol) or [mol] for mol in products]
+    prods_b = [spc.mol_list or [spc.mol] for spc in p_species]
+    if len(prods_a) == 1:
+        prod_a = prods_a[0]
+        prod_b = prods_b[0]
+        for mol_a in prod_a:
+            if any(mol_b.is_isomorphic(mol_a) for mol_b in prod_b):
+                return True
+    if len(products) == 2:
+        isomorphic = [False, False]
+        for i, prod_a in enumerate(prods_a):
+            skip = False
+            for prod_b in prods_b:
+                if skip:
+                    break
+                for mol_a in prod_a:
+                    if any(mol_b.is_isomorphic(mol_a) for mol_b in prod_b):
+                        isomorphic[i] = True
+                        skip = True
+        return all(isomorphic)
+    return False
+
+
+# def get_all_reactions_paths(rxn: 'ARCReaction') -> List['ARCReaction']:
+#     """
+#     Get all possible reaction paths with labeled atoms for a given ARC reaction.
+#
+#     Args:
+#         rxn ('ARCReaction'): The ARC reaction object.
+#
+#     Returns:
+#         List['ARCReaction']: A list of reactions, each represents a possible reaction path.
+#     """
+#     reaction_paths = list()
+#     for reactant in rxn.get_reactants_and_products(arc=True, return_copies=True)[0]:
+#         all_reactions.extend(reactant.generate_reactions())
+#     return all_reactions
+
+
+def get_all_families(rmg_family_set: Union[List[str], str] = 'default',
+                     consider_rmg_families: bool = True,
+                     consider_arc_families: bool = True,
+                     ) -> List[str]:
+    """
+    Get all available RMG and ARC families.
+
+    Args:
+        rmg_family_set (Union[List[str], str], optional): The RMG family set to use.
+        consider_rmg_families (bool, optional): Whether to consider RMG's families.
+        consider_arc_families (bool, optional): Whether to consider ARC's custom families.
+
+    Returns:
+        List[str]: A list of all available families.
+    """
+    rmg_families, arc_families = list(), list()
+    if consider_rmg_families:
+        family_sets = get_rmg_recommended_family_sets()
+        if not isinstance(rmg_families, list) and rmg_family_set not in list(family_sets) + ['all']:
+            raise ValueError(f'Invalid RMG family set: {rmg_family_set}')
+        if rmg_family_set == 'all':
+            for family_set_label, families in family_sets.items():
+                if 'surface' not in family_set_label:
+                    rmg_families.extend(list(families))
+        else:
+            rmg_families = list(family_sets[rmg_family_set]) \
+                if isinstance(rmg_family_set, str) and rmg_family_set in family_sets else rmg_family_set
+    if consider_arc_families:
+        for family in os.listdir(ARC_FAMILIES_PATH):
+            if family.startswith('.') or family.startswith('_'):
+                continue
+            arc_families.append(os.path.splitext(family)[0])
+    return rmg_families + arc_families
+
+
+def get_rmg_recommended_family_sets() -> Dict[str, str]:
+    """
+    Get the recommended RMG family sets from RMG-database/input/kinetics/families/recommended.py.
+
+    Returns:
+        Dict[str, str]: The recommended RMG family sets.
+    """
+    family_sets = dict()
+    recommended_path = os.path.join(RMG_DB_PATH, 'input', 'kinetics', 'families', 'recommended.py')
+    if not os.path.isfile(recommended_path):
+        raise FileNotFoundError(f'Could not find the recommended RMG families file at {recommended_path}')
+    with open(recommended_path, 'r') as f:
+        recommended_content = f.read()
+    dict_strings = re.findall(r'(\w+)\s*=\s*\{[^}]*\}', recommended_content, re.DOTALL)
+    for dict_name in dict_strings:
+        pattern = rf'{dict_name}\s*=\s*(\{{[^}}]*\}})'
+        match = re.search(pattern, recommended_content, re.DOTALL)
+        if match:
+            dict_str = match.group(1)
+            family_sets[dict_name] = ast.literal_eval(dict_str)
+    return family_sets
+
+
+def add_labels_to_molecule(mol: 'Molecule',   # revisit, copilot, and test
+                           isomorphic_subgraph: dict,
+                           ) -> 'Molecule':
+    """
+    Add atom labels to a molecule based on an isomorphic subgraph.
+
+    Args:
+         mol ('Molecule'): The molecule to add labels to.
+         isomorphic_subgraph (dict): A dictionary representing the isomorphic subgraph. E.g.::
+                                         {<Atom 'C'>: <GroupAtom [*2 'R!H']>,
+                                          <Atom 'C.'>: <GroupAtom [*1 'R!H']>,
+                                          <Atom 'H'>: <GroupAtom [*3 'H']>
+                                        }
+
+    Returns:
+         'Molecule': The molecule with atom labels added.
+    """
+    for atom_index, label in isomorphic_subgraph.items():
+        mol.atoms[atom_index].label = label
+    return mol
+
+
+def is_reversible(groups_as_lines: List[str]) -> bool:
+    """
+    Determine whether the reaction family is reversible.
+
+    Returns:
+        bool: Whether the reaction family is reversible.
+    """
+    for line in groups_as_lines:
+        if 'reversible = True' in line:
+            return True
+        if 'reversible = False' in line:
+            return False
+    return True
+
+
+def is_own_reverse(groups_as_lines: List[str]) -> bool:
+    """
+    Determine whether the reaction family's template also represents its own reverse.
+
+    Returns:
+        bool: Whether the reaction family's template also represents its own reverse.
+    """
+    for line in groups_as_lines:
+        if 'ownReverse=True' in line:
+            return True
+        if 'ownReverse=False' in line:
+            return False
+    return False
+
+
+def get_reactant_groups_from_template(groups_as_lines: List[str]) -> List[List[str]]:
+    """
+    Get the reactant groups from a template content string.
+    Descends the entries if a group is defined as an OR complex,
+    e.g.: group = "OR{Xtrirad_H, Xbirad_H, Xrad_H, X_H}"
+
+    Args:
+        groups_as_lines (List[str]): The template content string.
+
+    Returns:
+        List[List[str]]: The non-complex reactant groups.
+    """
+    reactant_labels = get_initial_reactant_labels_from_template(groups_as_lines)
+    result = list()
+    for reactant_label in reactant_labels:
+        if 'OR{' not in get_group_adjlist(groups_as_lines, entry_label=reactant_label):
+            result.append([reactant_label])
+        else:
+            stack = [reactant_label]
+            while any('OR{' in get_group_adjlist(groups_as_lines, entry_label=label) for label in stack):
+                label = stack.pop(0)
+                group_adjlist = get_group_adjlist(groups_as_lines, entry_label=label)
+                if 'OR{' not in group_adjlist:
+                    stack.append(label)
+                else:
+                    stack.extend(descent_complex_group(group_adjlist))
+            result.append(stack)
+    return result
+
+
+def get_product_num(groups_as_lines: List[str]) -> int:
+    """
+    Get the number of products from a template content string.
+
+    Args:
+        groups_as_lines (List[str]): The template content string.
+
+    Returns:
+        int: The number of products.
+    """
+    return len(get_initial_reactant_labels_from_template(groups_as_lines, products=True))
+
+
+def descent_complex_group(group: str) -> List[str]:
+    """
+    Descend a group if it is defined as an OR complex,
+    e.g.: group = "OR{Xtrirad_H, Xbirad_H, Xrad_H, X_H}".
+
+    Args:
+        group (str): The group to descend.
+
+    Returns:
+        List[str]: The non-complex reactant group labels, e.g.: ['Xtrirad_H', 'Xbirad_H', 'Xrad_H', 'X_H'].
+    """
+    if group.startswith('OR{') and group.endswith('}'):
+        group = group[3:-1].split(', ')
+    if isinstance(group, str):
+        group = [group]
+    return group
+
+
+def get_initial_reactant_labels_from_template(groups_as_lines: List[str],
+                                              products: bool = False,
+                                              ) -> List[str]:
+    """
+    Get the initial reactant labels from a template content string.
+    Does not descent the entries if the corresponding group is defined as an OR complex.
+
+    Args:
+        groups_as_lines (List[str]): The template content string.
+        products (bool, optional): Whether to get the product labels instead of the reactant labels.
+
+    Returns:
+        List[str]: The reactant groups.
+    """
+    labels = list()
+    for line in groups_as_lines:
+        match = re.search(r'products=\[(.*?)\]', line) if products else re.search(r'reactants=\[(.*?)\]', line)
+        if match:
+            labels = match.group(1).replace('"', '').split(', ')
+            break
+    return labels
+
+
+def get_recipe_actions(groups_as_lines: List[str]) -> List[List[str]]:
+    """
+    Get the recipe actions from a template content string.
+
+    Args:
+        groups_as_lines (List[str]): The template content string.
+
+    Returns:
+        List[List[str]]: The recipe actions.
+    """
+    actions = []
+    for i in range(len(groups_as_lines)):
+        if 'recipe(actions=[' in groups_as_lines[i]:
+            j = 0
+            while '])' not in groups_as_lines[i + 1 + j]:
+                if "['" in groups_as_lines[i + 1 + j]:
+                    actions.append(ast.literal_eval(groups_as_lines[i + 1 + j].strip())[0])
+                j += 1
+            break
+    return actions
+
+
+def get_entries(groups_as_lines: List[str],
+                entry_labels: List[str],
+                ) -> Dict[str, str]:
+    """
+    Get the requested entries grom a template content string.
+
+    Args:
+        groups_as_lines (List[str]): The template content string.
+        entry_labels (List[str]): The entry labels to extract.
+
+    Returns:
+        Dict[str, str]: The extracted entries, keys are the labels, values are the groups.
+    """
+    groups_str = ''.join(groups_as_lines)
+    entries = re.findall(r'entry\((.*?)\)', groups_str, re.DOTALL)
+    specific_entries = dict()
+    for i, entry in enumerate(entries):
+        label_match = re.search(r'label = "(.*?)"', entry)
+        group_match = re.search(r'group =(.*?)(?=\w+ =)', entry, re.DOTALL)
+        if label_match is not None and group_match is not None and label_match.group(1) in entry_labels:
+            specific_entries[label_match.group(1)] = clean_text(group_match.group(1))
+        if i > 2000:
+            break
+    return specific_entries
+
+
+def get_group_adjlist(groups_as_lines: List[str],
+                      entry_label: str,
+                      ) -> str:
+    """
+    Get the corresponding group value for the given entry label.
+
+    Args:
+        groups_as_lines (List[str]): The template content string.
+        entry_label (str): The entry label to extract.
+
+    Returns:
+        str: The extracted group.
+    """
+    specific_entries = get_entries(groups_as_lines, entry_labels=[entry_label])
+    return specific_entries[entry_label]
+
+
+def get_isomorphic_subgraph(isomorphic_subgraph_1: dict,
+                            isomorphic_subgraph_2: dict,
+                            mol_1: 'Molecule',
+                            mol_2: 'Molecule',
+                            ) -> dict:
+    """
+    Get the isomorphic subgraph from two isomorphic subgraphs and the corresponding molecules.
+
+    Args:
+        isomorphic_subgraph_1 (dict): The isomorphic subgraph of the first molecule.
+        isomorphic_subgraph_2 (dict): The isomorphic subgraph of the second molecule.
+        mol_1 ('Molecule'): The first molecule.
+        mol_2 ('Molecule'): The second molecule.
+
+    Returns:
+        dict: The isomorphic subgraph which is a dict map of atom indices and group labels.
+              E.g.: {0: '*3', 4: '*1', 7: '*2'}
+    """
+    isomorphic_subgraph = dict()
+    len_mol_1 = len(mol_1.atoms)
+    for atom, group_atom in isomorphic_subgraph_1.items():
+        isomorphic_subgraph[mol_1.atoms.index(atom)] = group_atom.label
+    for atom, group_atom in isomorphic_subgraph_2.items():
+        isomorphic_subgraph[mol_2.atoms.index(atom) + len_mol_1] = group_atom.label
+    return isomorphic_subgraph
diff --git a/arc/reaction/family_test.py b/arc/reaction/family_test.py
new file mode 100644
index 0000000000..f80c3d6efa
--- /dev/null
+++ b/arc/reaction/family_test.py
@@ -0,0 +1,923 @@
+#!/usr/bin/env python3
+# encoding: utf-8
+
+"""
+This module contains unit tests of the arc.reaction.family module
+"""
+
+import os
+import unittest
+
+from rmgpy.molecule import Group, Molecule
+
+from arc.common import generate_resonance_structures
+from arc.reaction.family import (ReactionFamily,
+                                 ARC_FAMILIES_PATH,
+                                 RMG_DB_PATH,
+                                 add_labels_to_molecule,
+                                 check_product_isomorphism,
+                                 descent_complex_group,
+                                 determine_possible_reaction_products_from_family,
+                                 get_reaction_family_products,
+                                 get_all_families,
+                                 get_entries,
+                                 get_group_adjlist,
+                                 get_initial_reactant_labels_from_template,
+                                 get_isomorphic_subgraph,
+                                 get_product_num,
+                                 get_reactant_groups_from_template,
+                                 get_recipe_actions,
+                                 get_rmg_recommended_family_sets,
+                                 is_own_reverse,
+                                 is_reversible,
+                                 )
+from arc.reaction.reaction import ARCReaction
+from arc.species.species import ARCSpecies
+
+
+class TestReactionFamily(unittest.TestCase):
+    """
+    Contains unit tests for the arc reaction family module
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """
+        A method that is run before all unit tests in this class.
+        """
+        cls.maxDiff = None
+
+    def test_rmgdb_path(self):
+        """Test finding the RMG-database path"""
+        self.assertIn('RMG-database', RMG_DB_PATH)
+        self.assertTrue(os.path.isdir(RMG_DB_PATH))
+
+    def test_arc_families_path(self):
+        """Test finding the ARC families folder path"""
+        self.assertIn('ARC', ARC_FAMILIES_PATH)
+        self.assertIn('data', ARC_FAMILIES_PATH)
+        self.assertIn('families', ARC_FAMILIES_PATH)
+        self.assertTrue(os.path.isdir(ARC_FAMILIES_PATH))
+
+    def test_get_reaction_family_products_abstraction(self):
+        """Test determining the reaction family using product dicts"""
+        rxn_0a = ARCReaction(r_species=[ARCSpecies(label='CH4', smiles='C'), ARCSpecies(label='O2', smiles='[O][O]')],
+                             p_species=[ARCSpecies(label='CH3', smiles='[CH3]'),
+                                        ARCSpecies(label='HO2', smiles='O[O]')])
+        products = get_reaction_family_products(rxn_0a)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('X_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 1, '*3': 5},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('X_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 1, '*3': 6},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('X_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 2, '*3': 5},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('X_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 2, '*3': 6},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('X_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 3, '*3': 5},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('X_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 3, '*3': 6},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('X_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 4, '*3': 5},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('X_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 4, '*3': 6},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")]}]
+        self.assertEqual(products, expected_products)
+
+        ch4_xyz = """C      -0.00000000   -0.00000000    0.00000000
+H      -0.87497771   -0.55943190   -0.33815595
+H      -0.04050904    1.01567250   -0.39958464
+H       0.00816153    0.03824434    1.09149909
+H       0.90732523   -0.49448494   -0.35375850"""
+        o2_xyz = {'symbols': ('O', 'O'), 'isotopes': (16, 16), 'coords': ((0.0, 0.0, 0.6029), (0.0, 0.0, -0.6029))}
+        ch3_xyz = """C      -0.00000000   -0.00000000   -0.00000001
+H       1.04110758   -0.29553525    0.02584268
+H      -0.77665903   -0.75407986   -0.00884379
+H      -0.26444854    1.04961512   -0.01699888"""
+        ho2_xyz = """O      -0.15635718    0.45208323    0.00000000
+O       0.99456866   -0.18605915    0.00000000
+H      -0.83821148   -0.26602407    0.00000000"""
+
+        rxn_0b = ARCReaction(r_species=[ARCSpecies(label='CH4', xyz=ch4_xyz), ARCSpecies(label='O2', xyz=o2_xyz, multiplicity=3)],
+                             p_species=[ARCSpecies(label='CH3', xyz=ch3_xyz), ARCSpecies(label='HO2', xyz=ho2_xyz)],
+                             rmg_family_set=['H_Abstraction'])
+        products = get_reaction_family_products(rxn_0b)
+        expected_products = [{'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")],
+                              'label_map': {'*1': 0, '*2': 1, '*3': 5},
+                              'own_reverse': True, 'discovered_in_reverse': False},
+                             {'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")],
+                              'label_map': {'*1': 0, '*2': 1, '*3': 6},
+                              'own_reverse': True, 'discovered_in_reverse': False},
+                             {'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")],
+                              'label_map': {'*1': 0, '*2': 2, '*3': 5},
+                              'own_reverse': True, 'discovered_in_reverse': False},
+                             {'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")],
+                              'label_map': {'*1': 0, '*2': 2, '*3': 6},
+                              'own_reverse': True, 'discovered_in_reverse': False},
+                             {'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")],
+                              'label_map': {'*1': 0, '*2': 3, '*3': 5},
+                              'own_reverse': True, 'discovered_in_reverse': False},
+                             {'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")],
+                              'label_map': {'*1': 0, '*2': 3, '*3': 6},
+                              'own_reverse': True, 'discovered_in_reverse': False},
+                             {'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")],
+                              'label_map': {'*1': 0, '*2': 4, '*3': 5},
+                              'own_reverse': True, 'discovered_in_reverse': False},
+                             {'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="[CH3]")],
+                              'label_map': {'*1': 0, '*2': 4, '*3': 6},
+                              'own_reverse': True, 'discovered_in_reverse': False}]
+        self.assertEqual(products, expected_products)
+
+        rxn_1 = ARCReaction(reactants=['NH2', 'NH2'], products=['NH', 'NH3'],
+                            r_species=[ARCSpecies(label='NH2', smiles='[NH2]')],
+                            p_species=[ARCSpecies(label='NH', smiles='[NH]'), ARCSpecies(label='NH3', smiles='N')],
+                            rmg_family_set=['H_Abstraction'])
+        products = get_reaction_family_products(rxn_1)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('Xrad_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 1, '*3': 3},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="N"), Molecule(smiles="[NH]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('Xrad_H', 'Y_rad'),
+                              'label_map': {'*1': 0, '*2': 2, '*3': 3},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="N"), Molecule(smiles="[NH]")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('Y_rad', 'Xrad_H'),
+                              'label_map': {'*1': 3, '*2': 4, '*3': 0},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[NH]"), Molecule(smiles="N")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'H_Abstraction',
+                              'group_labels': ('Y_rad', 'Xrad_H'),
+                              'label_map': {'*1': 3, '*2': 5, '*3': 0},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="N"), Molecule(smiles="[NH]")]}]
+        self.assertEqual(products, expected_products)
+
+    def test_get_reaction_family_products_cyclic_ether_formation(self):
+        """Test determining the reaction family using product dicts"""
+        rxn_2f = ARCReaction(r_species=[ARCSpecies(label='C2H3O3', smiles='[CH2]C(=O)OO')],
+                             p_species=[ARCSpecies(label='C2H2O2', smiles='O=C1CO1'),
+                                        ARCSpecies(label='OH', smiles='[OH]')])
+        products = get_reaction_family_products(rxn_2f)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': 'Cyclic_Ether_Formation',
+                              'group_labels': 'R2OO',
+                              'label_map': {'*1': 0, '*2': 3, '*3': 4, '*4': 1},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="[OH]"), Molecule(smiles="O=C1CO1")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'Cyclic_Ether_Formation',
+                              'group_labels': 'R2OO',
+                              'label_map': {'*1': 0, '*2': 3, '*3': 4, '*4': 1},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="[OH]"), Molecule(smiles="O=C1CO1")]}]
+        self.assertEqual(products, expected_products)
+
+        rxn_2_r = ARCReaction(p_species=[ARCSpecies(label='C2H3O3', smiles='[CH2]C(=O)OO')],
+                              r_species=[ARCSpecies(label='C2H2O2', smiles='O=C1CO1'),
+                                         ARCSpecies(label='OH', smiles='[OH]')],
+                              rmg_family_set=['Cyclic_Ether_Formation'])
+        products = get_reaction_family_products(rxn_2_r)
+        expected_products = [{'discovered_in_reverse': True,
+                              'family': 'Cyclic_Ether_Formation',
+                              'group_labels': 'R2OO',
+                              'label_map': {'*1': 0, '*2': 3, '*3': 4, '*4': 1},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="[OH]"), Molecule(smiles="O=C1CO1")]},
+                             {'discovered_in_reverse': True,
+                              'family': 'Cyclic_Ether_Formation',
+                              'group_labels': 'R2OO',
+                              'label_map': {'*1': 0, '*2': 3, '*3': 4, '*4': 1},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="[OH]"), Molecule(smiles="O=C1CO1")]}]
+        self.assertEqual(products, expected_products)
+
+    def test_get_reaction_family_migration(self):
+        """Test determining the reaction family using product dicts"""
+        rxn_3 = ARCReaction(r_species=[ARCSpecies(label='CCC[O]', smiles='CCC[O]')],
+                            p_species=[ARCSpecies(label='C[CH]CO', smiles='C[CH]CO')],
+                            rmg_family_set=['intra_H_migration'])
+        products = get_reaction_family_products(rxn_3)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': 'intra_H_migration',
+                              'group_labels': 'R3Hall',
+                              'label_map': {'*1': 3, '*2': 1, '*3': 7, '*4': 2},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="C[CH]CO")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'intra_H_migration',
+                              'group_labels': 'R3Hall',
+                              'label_map': {'*1': 3, '*2': 1, '*3': 8, '*4': 2},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="C[CH]CO")]}]
+        self.assertEqual(products, expected_products)
+
+        rxn_8 = ARCReaction(r_species=[ARCSpecies(label='C3H7O2a', smiles='C[CH]COO')],
+                            p_species=[ARCSpecies(label='C3H7O2b', smiles='CC(O)C[O]')],
+                            rmg_family_set=['intra_OH_migration'])
+        products = get_reaction_family_products(rxn_8)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': 'intra_OH_migration',
+                              'group_labels': 'R2OOH',
+                              'label_map': {'*1': 1, '*2': 3, '*3': 4, '*4': 2},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="CC(O)C[O]")]}]
+        self.assertEqual(products, expected_products)
+
+        rxn_9 = ARCReaction(r_species=[ARCSpecies(label='R', smiles='C[CH]CCCC')],  # iso-teleological paths
+                            p_species=[ARCSpecies(label='P', smiles='[CH2]CCCCC')],
+                            rmg_family_set=['intra_H_migration'])
+        products = get_reaction_family_products(rxn_9)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': 'intra_H_migration',
+                              'group_labels': 'R5Hall',
+                              'label_map': {'*1': 1, '*2': 5, '*3': 16, '*4': 2, '*5': 4, '*6': 3},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[CH2]CCCCC")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'intra_H_migration',
+                              'group_labels': 'R5Hall',
+                              'label_map': {'*1': 1, '*2': 5, '*3': 17, '*4': 2, '*5': 4, '*6': 3},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[CH2]CCCCC")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'intra_H_migration',
+                              'group_labels': 'R5Hall',
+                              'label_map': {'*1': 1, '*2': 5, '*3': 18, '*4': 2, '*5': 4, '*6': 3},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[CH2]CCCCC")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'intra_H_migration',
+                              'group_labels': 'R2H',
+                              'label_map': {'*1': 1, '*2': 0, '*3': 6},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[CH2]CCCCC")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'intra_H_migration',
+                              'group_labels': 'R2H',
+                              'label_map': {'*1': 1, '*2': 0, '*3': 7},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[CH2]CCCCC")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'intra_H_migration',
+                              'group_labels': 'R2H',
+                              'label_map': {'*1': 1, '*2': 0, '*3': 8},
+                              'own_reverse': True,
+                              'products': [Molecule(smiles="[CH2]CCCCC")]}]
+        self.assertEqual(products, expected_products)
+
+    def test_get_reaction_family_ketoenol(self):
+        """Test determining the reaction family using product dicts"""
+        rxn_4f = ARCReaction(r_species=[ARCSpecies(label='HOCCOH', smiles='OC=CO')],
+                             p_species=[ARCSpecies(label='HOCCO', smiles='OCC=O')],
+                             rmg_family_set=['Ketoenol'])
+        products = get_reaction_family_products(rxn_4f)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': 'Ketoenol',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 2, '*2': 1, '*3': 0, '*4': 4},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CCO")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'Ketoenol',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 2, '*3': 3, '*4': 7},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CCO")]}]
+        self.assertEqual(products, expected_products)
+
+        rxn_4r = ARCReaction(r_species=[ARCSpecies(label='HOCCO', smiles='OCC=O')],
+                             p_species=[ARCSpecies(label='HOCCOH', smiles='OC=CO')],
+                             rmg_family_set=['Ketoenol'])
+        products = get_reaction_family_products(rxn_4r)
+        expected_products = [{'discovered_in_reverse': True,
+                              'family': 'Ketoenol',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 2, '*2': 1, '*3': 0, '*4': 4},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CCO")]},
+                             {'discovered_in_reverse': True,
+                              'family': 'Ketoenol',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 2, '*3': 3, '*4': 7},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CCO")]}]
+        self.assertEqual(products, expected_products)
+
+    def test_get_reaction_family_insertion(self):
+        """Test determining the reaction family using product dicts"""
+        # Test a family that is bimolecular, but the two reactants are defined as a single group in the recipe:
+        rxn_5f = ARCReaction(r_species=[ARCSpecies(label='CO2', smiles='O=C=O'),
+                                        ARCSpecies(label='H2', smiles='[H][H]')],
+                             p_species=[ARCSpecies(label='CHOOH', smiles='O=CO')],
+                             rmg_family_set=['1,3_Insertion_CO2'])
+        products = get_reaction_family_products(rxn_5f)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': '1,3_Insertion_CO2',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 0, '*3': 4, '*4': 3},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CO")]},
+                             {'discovered_in_reverse': False,
+                              'family': '1,3_Insertion_CO2',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 0, '*3': 3, '*4': 4},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CO")]},
+                             {'discovered_in_reverse': False,
+                              'family': '1,3_Insertion_CO2',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 2, '*3': 4, '*4': 3},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CO")]},
+                             {'discovered_in_reverse': False,
+                              'family': '1,3_Insertion_CO2',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 2, '*3': 3, '*4': 4},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CO")]}]
+        self.assertEqual(products, expected_products)
+
+        rxn_5r = ARCReaction(r_species=[ARCSpecies(label='CHOOH', smiles='O=CO')],
+                             p_species=[ARCSpecies(label='CO2', smiles='O=C=O'),
+                                        ARCSpecies(label='H2', smiles='[H][H]')],
+                             rmg_family_set=['1,3_Insertion_CO2'])
+        products = get_reaction_family_products(rxn_5r)
+        expected_products = [{'discovered_in_reverse': True,
+                              'family': '1,3_Insertion_CO2',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 0, '*3': 4, '*4': 3},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CO")]},
+                             {'discovered_in_reverse': True,
+                              'family': '1,3_Insertion_CO2',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 0, '*3': 3, '*4': 4},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CO")]},
+                             {'discovered_in_reverse': True,
+                              'family': '1,3_Insertion_CO2',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 2, '*3': 4, '*4': 3},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CO")]},
+                             {'discovered_in_reverse': True,
+                              'family': '1,3_Insertion_CO2',
+                              'group_labels': 'Root',
+                              'label_map': {'*1': 1, '*2': 2, '*3': 3, '*4': 4},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="O=CO")]}]
+        self.assertEqual(products, expected_products)
+
+    def test_get_reaction_family_elimination(self):
+        """Test determining the reaction family using product dicts"""
+        rxn_6 = ARCReaction(r_species=[ARCSpecies(label='C2H3O3', smiles='CC(=O)O[O]')],
+                            p_species=[ARCSpecies(label='C2H2O', smiles='C=C=O'),
+                                       ARCSpecies(label='HO2', smiles='O[O]')],
+                            rmg_family_set=['HO2_Elimination_from_PeroxyRadical'])
+        products = get_reaction_family_products(rxn_6)
+        expected_products = [{'discovered_in_reverse': False,
+                              'family': 'HO2_Elimination_from_PeroxyRadical',
+                              'group_labels': 'R2OO',
+                              'label_map': {'*1': 0, '*2': 1, '*3': 3, '*4': 4, '*5': 5},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="C=C=O"), Molecule(smiles="[O]O")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'HO2_Elimination_from_PeroxyRadical',
+                              'group_labels': 'R2OO',
+                              'label_map': {'*1': 0, '*2': 1, '*3': 3, '*4': 4, '*5': 6},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="C=C=O"), Molecule(smiles="[O]O")]},
+                             {'discovered_in_reverse': False,
+                              'family': 'HO2_Elimination_from_PeroxyRadical',
+                              'group_labels': 'R2OO',
+                              'label_map': {'*1': 0, '*2': 1, '*3': 3, '*4': 4, '*5': 7},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="[O]O"), Molecule(smiles="C=C=O")]}]
+        self.assertEqual(products, expected_products)
+
+    def test_get_reaction_family_r_add_mult_bond(self):
+        """Test determining the reaction family using product dicts"""
+        spc_1 = ARCSpecies(label='C2H3O3', smiles='[CH2]C(=O)OO')
+        spc_1.mol_list = generate_resonance_structures(object_=spc_1.mol, keep_isomorphic=True)
+        rxn_7 = ARCReaction(r_species=[spc_1],
+                            p_species=[ARCSpecies(label='C2H2O', smiles='C=C=O'),
+                                       ARCSpecies(label='HO2', smiles='O[O]')],
+                            rmg_family_set=['R_Addition_MultipleBond'])
+        products = get_reaction_family_products(rxn_7)
+        expected_products = [{'discovered_in_reverse': True,
+                              'family': 'R_Addition_MultipleBond',
+                              'group_labels': ('R_R', 'OJ_sec'),
+                              'label_map': {'*1': 1, '*2': 0, '*3': 6},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="[CH2]C(=O)OO")]},
+                             {'discovered_in_reverse': True,
+                              'family': 'R_Addition_MultipleBond',
+                              'group_labels': ('R_R', 'OJ_sec'),
+                              'label_map': {'*1': 1, '*2': 2, '*3': 6},
+                              'own_reverse': False,
+                              'products': [Molecule(smiles="C=C([O])OO")]}]
+        self.assertEqual(products, expected_products)
+
+    def test_get_reaction_family_products_considering_resonance(self):
+        """Test determining the reaction family using product dicts for the non-trivial resonance structure"""
+        rxn_0a = ARCReaction(r_species=[ARCSpecies(label='R1', smiles='CC(C=S)S'),
+                                        ARCSpecies(label='R2', smiles='C=C[CH]C')],
+                             p_species=[ARCSpecies(label='P1', smiles='[S]C=C(S)C'),
+                                        ARCSpecies(label='P2', smiles='C=CCC')],
+                             rmg_family_set=['H_Abstraction'])
+        products = get_reaction_family_products(rxn_0a)
+        expected_products = [{'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="C=CCC"), Molecule(smiles="C[C](C=S)S")],
+                              'label_map': {'*1': 1, '*2': 8, '*3': 13},
+                              'own_reverse': True, 'discovered_in_reverse': False},
+                             {'family': 'H_Abstraction', 'group_labels': ('X_H', 'Y_rad'),
+                              'products': [Molecule(smiles="C=CCC"), Molecule(smiles="C[C](C=S)S")],
+                              'label_map': {'*1': 1, '*2': 8, '*3': 13},
+                              'own_reverse': True, 'discovered_in_reverse': False}]
+        self.assertEqual(products, expected_products)
+
+    def test_determine_possible_reaction_products_from_family(self):
+        """Test determining the possible reaction products from a family"""
+        rxn_1 = ARCReaction(r_species=[ARCSpecies(label='nC3H7', smiles='[CH2]CC')],
+                            p_species=[ARCSpecies(label='iC3H7', smiles='C[CH]C')],
+                            rmg_family_set=['intra_H_migration'])
+        product_dicts = determine_possible_reaction_products_from_family(rxn_1, family_label='intra_H_migration')
+        expected_product_dicts = [{'discovered_in_reverse': False,
+                                   'family': 'intra_H_migration',
+                                   'group_labels': 'R3Hall',
+                                   'label_map': {'*1': 0, '*4': 1, '*2': 2, '*3': 7},
+                                   'own_reverse': True,
+                                   'products': [Molecule(smiles="[CH2]CC")]},
+                                  {'discovered_in_reverse': False,
+                                   'family': 'intra_H_migration',
+                                   'group_labels': 'R3Hall',
+                                   'label_map': {'*1': 0, '*4': 1, '*2': 2, '*3': 8},
+                                   'own_reverse': True,
+                                   'products': [Molecule(smiles="[CH2]CC")]},
+                                  {'discovered_in_reverse': False,
+                                   'family': 'intra_H_migration',
+                                   'group_labels': 'R3Hall',
+                                   'label_map': {'*1': 0, '*4': 1, '*2': 2, '*3': 9},
+                                   'own_reverse': True,
+                                   'products': [Molecule(smiles="[CH2]CC")]},
+                                  {'discovered_in_reverse': False,
+                                   'family': 'intra_H_migration',
+                                   'group_labels': 'R2H',
+                                   'label_map': {'*1': 0, '*2': 1, '*3': 5},
+                                   'own_reverse': True,
+                                   'products': [Molecule(smiles="C[CH]C")]},
+                                  {'discovered_in_reverse': False,
+                                   'family': 'intra_H_migration',
+                                   'group_labels': 'R2H',
+                                   'label_map': {'*1': 0, '*2': 1, '*3': 6},
+                                   'own_reverse': True,
+                                   'products': [Molecule(smiles="C[CH]C")]}]
+        self.assertEqual(product_dicts, expected_product_dicts)
+
+    def test_check_product_isomorphism(self):
+        """Test checking product isomorphism"""
+        product_1 = Molecule(smiles='C[CH]C')
+        product_2 = ARCSpecies(label='S1', mol=Molecule(smiles='C[CH]C'))
+        self.assertTrue(check_product_isomorphism([product_1], [product_2]))
+        product_2 = ARCSpecies(label='S1', mol=Molecule(smiles='[CH2]CC'))
+        self.assertFalse(check_product_isomorphism([product_1], [product_2]))
+
+        product_1 = Molecule(smiles='C=C[O]')
+        product_2 = ARCSpecies(label='S1', mol=Molecule(smiles='[CH2]C=O'))
+        self.assertTrue(check_product_isomorphism([product_1], [product_2]))
+
+        product_1 = Molecule(smiles='C[C](C=S)S')
+        product_2 = ARCSpecies(label='S1', mol=Molecule(smiles='[S]C=C(S)C'))
+        self.assertTrue(check_product_isomorphism([product_1], [product_2]))
+
+        product_1 = Molecule(smiles='[CH2]C(C=S)S')
+        self.assertFalse(check_product_isomorphism([product_1], [product_2]))
+
+        products = [Molecule(smiles="[CH2]C(C=S)S")]
+        p_species = [ARCSpecies(label="P1", smiles="[S]C=C(S)C", is_ts=False, multiplicity=2, charge=0),]
+        self.assertFalse(check_product_isomorphism(products, p_species))
+
+        products = [Molecule(smiles="C=CCC"), Molecule(smiles="[CH2]C(C=S)S")]
+        p_species = [ARCSpecies(label="P1", smiles="[S]C=C(S)C", is_ts=False, multiplicity=2, charge=0),
+                     ARCSpecies(label="P2", smiles="C=CCC", is_ts=False, multiplicity=1, charge=0)]
+        self.assertFalse(check_product_isomorphism(products, p_species))
+
+    def test_get_all_families(self):
+        """Test getting all families from RMG and/or ARC"""
+        families = get_all_families(consider_arc_families=False)
+        self.assertIsInstance(families, list)
+        self.assertIn('1,3_Insertion_ROR', families)
+        self.assertIn('6_membered_central_C-C_shift', families)
+        self.assertIn('H_Abstraction', families)
+        self.assertIn('intra_H_migration', families)
+        self.assertIn('Retroene', families)
+        self.assertIn('Ketoenol', families)
+        self.assertIn('intra_NO2_ONO_conversion', families)
+        self.assertIn('intra_OH_migration', families)
+        families = get_all_families(consider_rmg_families=False)
+        self.assertIsInstance(families, list)
+        self.assertIn('hydrolysis', families)
+
+    def test_get_rmg_recommended_family_sets(self):
+        """Test getting RMG recommended family sets"""
+        recommended_families = get_rmg_recommended_family_sets()
+        self.assertIn('default', recommended_families)
+        self.assertIn('ch_pyrolysis', recommended_families)
+        self.assertIn('liquid_peroxide', recommended_families)
+
+    def test_load(self):
+        """Test loading a reaction family from the RMG database"""
+        fam_1 = ReactionFamily('1,3_NH3_elimination')
+        self.assertEqual(fam_1.label, '1,3_NH3_elimination')
+        self.assertTrue(fam_1.reversible)
+        self.assertFalse(fam_1.own_reverse)
+        self.assertEqual(fam_1.reactants, [['Root']])
+        self.assertEqual(fam_1.product_num, 2)
+        self.assertEqual(fam_1.entries, {'Root': """1 *1 N   u0 p1 c0 {2,S} {4,S} {5,S}
+2 *2 R!H u0 c0 {1,S} {3,[S,D]}
+3 *3 R!H u0 c0 {2,[S,D]} {6,S}
+4    H   u0 p0 c0 {1,S}
+5    H   u0 p0 c0 {1,S}
+6 *4 H   u0 p0 c0 {3,S}"""})
+        self.assertEqual(fam_1.actions, [['FORM_BOND', '*1', 1, '*4'],
+                                         ['BREAK_BOND', '*1', 1, '*2'],
+                                         ['BREAK_BOND', '*3', 1, '*4'],
+                                         ['CHANGE_BOND', '*2', 1, '*3']])
+
+        fam_2 = ReactionFamily('Retroene')
+        self.assertEqual(fam_2.label, 'Retroene')
+        self.assertTrue(fam_2.reversible)
+        self.assertFalse(fam_2.own_reverse)
+        self.assertEqual(fam_2.reactants, [['Root']])
+        self.assertEqual(fam_2.product_num, 2)
+        self.assertEqual(fam_2.entries, {'Root': """1 *3 R!H u0 {2,S} {3,[S,D]}
+2 *4 R!H u0 {1,S} {4,[S,D]}
+3 *2 R!H u0 {1,[S,D]} {5,[D,T,B]}
+4 *5 R!H u0 {2,[S,D]} {6,S}
+5 *1 R!H u0 {3,[D,T,B]}
+6 *6 H   u0 {4,S}"""})
+        self.assertEqual(fam_2.actions, [['CHANGE_BOND', '*1', -1, '*2'],
+                                         ['BREAK_BOND', '*5', 1, '*6'],
+                                         ['BREAK_BOND', '*3', 1, '*4'],
+                                         ['FORM_BOND', '*1', 1, '*6'],
+                                         ['CHANGE_BOND', '*2', 1, '*3'],
+                                         ['CHANGE_BOND', '*4', 1, '*5']])
+
+        fam_3 = ReactionFamily('H_Abstraction')
+        self.assertEqual(fam_3.label, 'H_Abstraction')
+        self.assertTrue(fam_3.reversible)
+        self.assertTrue(fam_3.own_reverse)
+        self.assertEqual(fam_3.reactants, [['Xrad_H', 'X_H', 'C_quartet_H', 'C_doublet_H', 'CH2_triplet_H',
+                                            'CH2_singlet_H', 'NH_triplet_H', 'NH_singlet_H'],
+                                           ['Y_rad', 'Y_1centerbirad', 'N_atom_quartet', 'N_atom_doublet',
+                                            'CH_quartet', 'CH_doublet', 'C_quintet', 'C_triplet']])
+        self.assertEqual(fam_3.product_num, 2)
+        self.assertEqual(fam_3.entries, {'CH2_singlet_H': '1 *1 C u0 p1 {2,S} {3,S}\n2 *2 H u0 {1,S}\n3    H u0 {1,S}',
+                                         'CH2_triplet_H': '1 *1 Cs u2 {2,S} {3,S}\n2 *2 H  u0 {1,S}\n3    H  u0 {1,S}',
+                                         'CH_doublet': '1 *3 C u1 p1 {2,S}\n2    H u0 {1,S}',
+                                         'CH_quartet': '1 *3 C u3 p0 {2,S}\n2    H u0 p0 {1,S}',
+                                         'C_doublet_H': '1 *1 C u1 p1 {2,S}\n2 *2 H u0 p0 {1,S}',
+                                         'C_quartet_H': '1 *1 C u3 p0 {2,S}\n2 *2 H u0 p0 {1,S}',
+                                         'C_quintet': '1 *3 C u4 p0',
+                                         'C_triplet': '1 *3 C u2 p1',
+                                         'NH_singlet_H': '1 *1 N u0 p2 {2,S}\n2 *2 H u0 {1,S}',
+                                         'NH_triplet_H': '1 *1 N u2 p1 {2,S}\n2 *2 H u0 {1,S}',
+                                         'N_atom_doublet': '1 *3 N u1 p2',
+                                         'N_atom_quartet': '1 *3 N u3 p1',
+                                         'X_H': '1 *1 R u0 {2,S}\n2 *2 H u0 {1,S}',
+                                         'Xrad_H': '1 *1 R!H u1 {2,S}\n2 *2 H   u0 {1,S}',
+                                         'Y_1centerbirad': '1 *3 [Cs,Cd,CO,CS,O,S,N] u2',
+                                         'Y_rad': '1 *3 R u1'})
+        self.assertEqual(fam_3.actions, [['BREAK_BOND', '*1', 1, '*2'],
+                                         ['FORM_BOND', '*2', 1, '*3'],
+                                         ['GAIN_RADICAL', '*1', '1'],
+                                         ['LOSE_RADICAL', '*3', '1']])
+
+    def test_generate_products(self):
+        """Test generating products from a family reaction"""
+        nc3h7_xyz = """C       1.37804814    0.27791806   -0.19510872
+C       0.17556863   -0.34036372    0.43264370
+C      -0.83187347    0.70417963    0.88324345
+H       2.32472321   -0.25030138   -0.17788282
+H       1.28333786    1.14668473   -0.83693739
+H      -0.29365347   -1.02041871   -0.28598479
+H       0.48921065   -0.93758132    1.29559484
+H      -1.19281046    1.29833383    0.03681883
+H      -1.69637465    0.21982206    1.34848803
+H      -0.39179140    1.38837612    1.61666966"""  # C_0 is the radical site that is labeled *1 in intra_H_migration
+        reactants = [ARCSpecies(label='nC3H7', smiles='[CH2]CC', xyz=nc3h7_xyz)]
+        fam_1 = ReactionFamily('intra_H_migration')
+        products = fam_1.generate_products(reactants=reactants)
+        # {'R2H': [[Molecule(smiles="C[CH]C")], [Molecule(smiles="C[CH]C")]],
+        #  'R3Hall': [[Molecule(smiles="[CH2]CC")], [Molecule(smiles="[CH2]CC")], [Molecule(smiles="[CH2]CC")]]}
+        self.assertEqual(list(products.keys()), ['R3Hall', 'R2H'])
+        self.assertEqual(len(products['R2H']), 2)
+        self.assertEqual(len(products['R3Hall']), 3)
+        mol_2 = Molecule(smiles='C[CH]C')
+        mol_3 = Molecule(smiles='CC[CH2]')
+        for i, (mol, isomorphic_subgraph) in enumerate(products['R2H']):
+            self.assertTrue(mol[0].is_isomorphic(mol_2))
+            self.assertEqual(isomorphic_subgraph, {1: '*2', 0: '*1', 5 + i: '*3'})
+        for i, (mol, isomorphic_subgraph) in enumerate(products['R3Hall']):
+            self.assertTrue(mol[0].is_isomorphic(mol_3))
+            self.assertEqual(isomorphic_subgraph, {1: '*4', 2: '*2', 0: '*1', 7 + i: '*3'})
+
+        reactants = [ARCSpecies(label='OH', smiles='[OH]'), ARCSpecies(label='NCC', smiles='NCC')]
+        fam_2 = ReactionFamily('H_Abstraction')
+        products = fam_2.generate_products(reactants=reactants)
+        # {('Y_rad', 'X_H'): [[Molecule(smiles="CC[NH]"), Molecule(smiles="O")],
+        #                     [Molecule(smiles="CC[NH]"), Molecule(smiles="O")],
+        #                     [Molecule(smiles="C[CH]N"), Molecule(smiles="O")],
+        #                     [Molecule(smiles="C[CH]N"), Molecule(smiles="O")],
+        #                     [Molecule(smiles="[CH2]CN"), Molecule(smiles="O")],
+        #                     [Molecule(smiles="[CH2]CN"), Molecule(smiles="O")],
+        #                     [Molecule(smiles="O"), Molecule(smiles="[CH2]CN")]]}
+        self.assertEqual(list(products.keys()), [('Y_rad', 'X_H')])
+        self.assertEqual(len(products[('Y_rad', 'X_H')]), 7)
+        water = Molecule(smiles='O')
+        mol_1 = Molecule(smiles='CC[NH]')
+        mol_2 = Molecule(smiles='C[CH]N')
+        mol_3 = Molecule(smiles='[CH2]CN')
+        isomorphism_count = {1: 0, 2: 0, 3: 0}
+        for i, prod_list in enumerate(products[('Y_rad', 'X_H')]):
+            self.assertEqual(len(prod_list), 2)
+            self.assertEqual(len(prod_list[0]), 2)
+            self.assertTrue(any([mol.is_isomorphic(water) for mol in prod_list[0]]))  # continue fixing tests, your on thwe right path, then implement this atom label map in functions
+            if any([mol.is_isomorphic(mol_1) for mol in prod_list[0]]):
+                isomorphism_count[1] += 1
+            if any([mol.is_isomorphic(mol_2) for mol in prod_list[0]]):
+                isomorphism_count[2] += 1
+            if any([mol.is_isomorphic(mol_3) for mol in prod_list[0]]):
+                isomorphism_count[3] += 1
+            self.assertEqual(prod_list[1][5 + i], '*2')
+        self.assertEqual(isomorphism_count, {1: 2, 2: 2, 3: 3})
+
+        reactants = [ARCSpecies(label='CCNO2', smiles='CC[N+](=O)[O-]')]
+        fam_3 = ReactionFamily('intra_NO2_ONO_conversion')
+        products = fam_3.generate_products(reactants=reactants)
+        self.assertEqual(list(products.keys()), ['RNO2'])
+        self.assertEqual(len(products['RNO2']), 1)
+
+    def test_apply_recipe(self):
+        """Test applying a recipe to a reaction"""
+        enol_xyz = """N      -1.08230641   -0.01219735   -0.71533019
+C      -0.39232442   -0.36252334    0.40095597
+C       0.86960167   -0.07311243    0.72761693
+O       1.72832531    0.66102764   -0.04056470
+H      -0.67544356    0.53998289   -1.45605881
+H      -2.04604227   -0.31325832   -0.81723278
+H      -0.98464818   -0.95797120    1.09502934
+H       1.34031259   -0.39779001    1.64713425
+H       1.24252625    0.91583948   -0.84155142"""
+        fam_1 = ReactionFamily('Ketoenol')
+        reactant = ARCSpecies(label='enol', smiles='NC=CO', xyz=enol_xyz).mol
+        isomorphic_subgraph = {2: '*2', 3: '*3', 1: '*1', 8: '*4'}
+        updated_structures = fam_1.apply_recipe(mols=[reactant], isomorphic_subgraph=isomorphic_subgraph)
+        self.assertEqual(len(updated_structures), 1)
+        product = Molecule(smiles='NCC=O')
+        self.assertTrue(updated_structures[0].is_isomorphic(product))
+
+    def test_get_reactant_num(self):
+        """Test getting the number of reactants from a family"""
+        fam_1 = ReactionFamily('intra_H_migration')
+        self.assertEqual(fam_1.get_reactant_num(), 1)
+        fam_2 = ReactionFamily('1,3_Insertion_CO2')
+        self.assertEqual(fam_2.get_reactant_num(), 2)
+        fam_3 = ReactionFamily('H_Abstraction')
+        self.assertEqual(fam_3.get_reactant_num(), 2)
+
+    def test_add_labels_to_molecule(self):
+        """Test adding labels to a molecule"""
+        mol = Molecule().from_smiles('C')
+        labels = {0: '*1', 2: '*2'}
+        mol = add_labels_to_molecule(mol, labels)
+        self.assertEqual(mol.to_adjacency_list(), """1 *1 C u0 p0 c0 {2,S} {3,S} {4,S} {5,S}
+2    H u0 p0 c0 {1,S}
+3 *2 H u0 p0 c0 {1,S}
+4    H u0 p0 c0 {1,S}
+5    H u0 p0 c0 {1,S}
+""")
+
+    def test_is_reversible(self):
+        """Test checking if a reaction family is reversible"""
+        groups_as_lines = ['template(reactants=["Root"], products=["ketone"], ownReverse=False)',
+                           'reverse = "Ketone_To_Enol"', 'reversible = True']
+        self.assertTrue(is_reversible(groups_as_lines))
+        groups_as_lines = ['Template(reactants=["singlet"], products=["triplet"], ownReverse=False)',
+                           'reverse = "None"', 'reversible = False']
+        self.assertFalse(is_reversible(groups_as_lines))
+
+    def test_is_own_reverse(self):
+        """Test checking if a reaction family is its own reverse"""
+        groups_as_lines = ['template(reactants=["Root"], products=["ketone"], ownReverse=False)',
+                           'reverse = "Ketone_To_Enol"', 'reversible = True']
+        self.assertFalse(is_own_reverse(groups_as_lines))
+        groups_as_lines = ['template(reactants=["X_H_or_Xrad_H_Xbirad_H_Xtrirad_H", "Y_rad_birad_trirad_quadrad"], ' +
+                           'products=["X_H_or_Xrad_H_Xbirad_H_Xtrirad_H", "Y_rad_birad_trirad_quadrad"], ' +
+                           'ownReverse=True)', 'reversible = True']
+        self.assertTrue(is_own_reverse(groups_as_lines))
+
+    def test_get_product_num(self):
+        """Test getting the number of products from a family"""
+        groups_as_lines = ['template(reactants=["Root"], products=["ketone"], ownReverse=False)',
+                           'reverse = "Ketone_To_Enol"', 'reversible = True']
+        self.assertEqual(get_product_num(groups_as_lines), 1)
+        groups_as_lines = ['template(reactants=["X_H_or_Xrad_H_Xbirad_H_Xtrirad_H", "Y_rad_birad_trirad_quadrad"], ' +
+                           'products=["X_H_or_Xrad_H_Xbirad_H_Xtrirad_H", "Y_rad_birad_trirad_quadrad"], ' +
+                           'ownReverse=True)', 'reversible = True']
+        self.assertEqual(get_product_num(groups_as_lines), 2)
+
+    def test_get_reactant_groups_from_template(self):
+        """Test getting reactant groups from a template"""
+        fam_1 = ReactionFamily('6_membered_central_C-C_shift')
+        groups_path = os.path.join(RMG_DB_PATH, 'input', 'kinetics', 'families', fam_1.label, 'groups.py')
+        with open(groups_path, 'r') as f:
+            groups = f.readlines()
+        reactants_1 = get_reactant_groups_from_template(groups)
+        self.assertEqual(reactants_1, [['1_5_unsaturated_hexane']])
+
+        fam_2 = ReactionFamily('H_Abstraction')
+        groups_path = os.path.join(RMG_DB_PATH, 'input', 'kinetics', 'families', fam_2.label, 'groups.py')
+        with open(groups_path, 'r') as f:
+            groups = f.readlines()
+        reactants_2 = get_reactant_groups_from_template(groups)
+        expected_reactants = [['Xrad_H', 'X_H', 'C_quartet_H', 'C_doublet_H', 'CH2_triplet_H', 'CH2_singlet_H', 'NH_triplet_H', 'NH_singlet_H'],
+                              ['Y_rad', 'Y_1centerbirad', 'N_atom_quartet', 'N_atom_doublet', 'CH_quartet', 'CH_doublet', 'C_quintet', 'C_triplet']]
+        self.assertEqual(reactants_2, expected_reactants)
+
+        fam_3 = ReactionFamily('1,2-Birad_to_alkene')
+        groups_path = os.path.join(RMG_DB_PATH, 'input', 'kinetics', 'families', fam_3.label, 'groups.py')
+        with open(groups_path, 'r') as f:
+            groups = f.readlines()
+        reactants_3 = get_reactant_groups_from_template(groups)
+        expected_reactants = [['Y_12_13', 'Y_12_31', 'NOS', 'Y_12_00', 'Y_12_10', 'Y_12_20a', 'Y_12_20b', 'Y_12_30',
+                               'Y_12_40', 'Y_12_01', 'Y_12_02a', 'Y_12_02b', 'Y_12_03', 'Y_12_04', 'Y_12_11a',
+                               'Y_12_11b', 'Y_12_12a', 'Y_12_12b', 'Y_12_21a', 'Y_12_21b', 'Y_12_22a', 'Y_12_22b']]
+        self.assertEqual(reactants_3, expected_reactants)
+
+    def test_descent_complex_group(self):
+        """Test getting the specific groups of a complex group"""
+        self.assertEqual(descent_complex_group('N5c'), ['N5c'])
+        self.assertEqual(descent_complex_group("OR{Xtrirad_H, Xbirad_H, Xrad_H, X_H}"),
+                         ['Xtrirad_H', 'Xbirad_H', 'Xrad_H', 'X_H'])
+
+    def test_get_initial_reactant_labels_from_template(self):
+        """Test getting initial reactant labels from a template"""
+        content = ['template(reactants=["RnH"], products=["RnH"], ownReverse=True)']
+        reactants = get_initial_reactant_labels_from_template(content)
+        self.assertEqual(reactants, ['RnH'])
+        products = get_initial_reactant_labels_from_template(content, products=True)
+        self.assertEqual(products, ['RnH'])
+
+        content = ['template(reactants=["Root"], products=["RR", "NH3"], ownReverse=False)']
+        reactants = get_initial_reactant_labels_from_template(content)
+        self.assertEqual(reactants, ['Root'])
+        products = get_initial_reactant_labels_from_template(content, products=True)
+        self.assertEqual(products, ['RR', 'NH3'])
+
+        content = ['template(reactants=["X_H_or_Xrad_H_Xbirad_H_Xtrirad_H", "Y_rad_birad_trirad_quadrad"], '
+                   'products=["X_H_or_Xrad_H_Xbirad_H_Xtrirad_H", "Y_rad_birad_trirad_quadrad"], ownReverse=True)']
+        reactants = get_initial_reactant_labels_from_template(content)
+        self.assertEqual(reactants, ['X_H_or_Xrad_H_Xbirad_H_Xtrirad_H', 'Y_rad_birad_trirad_quadrad'])
+        products = get_initial_reactant_labels_from_template(content, products=True)
+        self.assertEqual(products, ['X_H_or_Xrad_H_Xbirad_H_Xtrirad_H', 'Y_rad_birad_trirad_quadrad'])
+
+    def test_get_recipe_actions(self):
+        """Test getting recipe actions"""
+        recipe_lines = [
+            "recipe(actions=[",
+            "['BREAK_BOND', '*1', 1, '*2'],",
+            "['FORM_BOND', '*2', 1, '*3'],",
+            "['GAIN_RADICAL', '*1', '1'],",
+            "['LOSE_RADICAL', '*3', '1'],",
+            "])"]
+        actions = get_recipe_actions(recipe_lines)
+        self.assertEqual(actions, [['BREAK_BOND', '*1', 1, '*2'],
+                                   ['FORM_BOND', '*2', 1, '*3'],
+                                   ['GAIN_RADICAL', '*1', '1'],
+                                   ['LOSE_RADICAL', '*3', '1']])
+
+        fam_1 = ReactionFamily('6_membered_central_C-C_shift')
+        groups_path = os.path.join(RMG_DB_PATH, 'input', 'kinetics', 'families', fam_1.label, 'groups.py')
+        with open(groups_path, 'r') as f:
+            groups = f.readlines()
+        actions = get_recipe_actions(groups)
+        self.assertEqual(actions, [['BREAK_BOND', '*3', 1, '*4'],
+                                   ['CHANGE_BOND', '*1', -1, '*2'],
+                                   ['CHANGE_BOND', '*5', -1, '*6'],
+                                   ['CHANGE_BOND', '*2', 1, '*3'],
+                                   ['CHANGE_BOND', '*4', 1, '*5'],
+                                   ['FORM_BOND', '*1', 1, '*6']])
+
+    def test_get_entries(self):
+        """Test getting entries from a family"""
+        fam_1 = ReactionFamily('1,3_Insertion_ROR')
+        groups_as_lines = fam_1.get_groups_file_as_lines()
+        entries = get_entries(groups_as_lines=groups_as_lines, entry_labels=['doublebond', 'cco_2H'])
+        self.assertEqual(entries, {'doublebond': 'OR{Cd_Cdd, Cdd_Cd, Cd_Cd, Sd_Cd, N1dc_N5ddc, N3d_Cd}',
+                                   'cco_2H': """1 *1 Cd        u0 {2,D} {3,S} {4,S}
+2 *2 Cdd       u0 {1,D} {5,D}
+3    H         u0 {1,S}
+4    H         u0 {1,S}
+5    [O2d,S2d] u0 {2,D}"""})
+
+    def test_get_isomorphic_subgraph(self):
+        """Test getting the isomorphic subgraph"""
+        oh_xyz = {'symbols': ('O', 'H'), 'isotopes': (16, 1), 'coords': ((0.0, 0.0, 0.6131), (0.0, 0.0, -0.6131))}
+        ncc_xyz = {'symbols': ('N', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H'),
+                   'isotopes': (14, 12, 12, 1, 1, 1, 1, 1, 1, 1),
+                   'coords': ((1.2562343261659277, 0.055282951474465256, -0.5803566480287667),
+                              (0.2433806820538858, -0.2998022593250662, 0.4048026179081362),
+                              (-1.1419715208061372, 0.05031794898903049, -0.10936163768735493),
+                              (0.30010122891852403, -1.3732777777516794, 0.6116620393221122),
+                              (0.4378838143353429, 0.23284176746008836, 1.3415344409291001),
+                              (-1.3668225970409684, -0.4847381186432614, -1.0382269930378532),
+                              (-1.2346536276957667, 1.1246102699428049, -0.30155738107540364),
+                              (-1.899948780117477, -0.22595560919578353, 0.6306294743856438),
+                              (1.224390390624704, 1.0579934139157359, -0.7603389078698333),
+                              (2.1814060835619262, -0.13727258686634466, -0.1987870048457775))}
+        spc_1 = ARCSpecies(label='OH', smiles='[OH]', xyz=oh_xyz)
+        spc_2 = ARCSpecies(label='NCC', smiles='NCC', xyz=ncc_xyz)
+        groups_as_lines = ReactionFamily('H_Abstraction').groups_as_lines
+        group_1 = Group().from_adjacency_list(get_group_adjlist(groups_as_lines=groups_as_lines, entry_label='Y_rad'))
+        group_2 = Group().from_adjacency_list(get_group_adjlist(groups_as_lines=groups_as_lines, entry_label='X_H'))
+        isomorphic_subgraphs_1 = spc_1.mol.find_subgraph_isomorphisms(other=group_1, save_order=True)
+        isomorphic_subgraphs_2 = spc_2.mol.find_subgraph_isomorphisms(other=group_2, save_order=True)
+        self.assertEqual(len(isomorphic_subgraphs_1), 1)
+        self.assertEqual(len(isomorphic_subgraphs_2), 7)
+        for key, val in isomorphic_subgraphs_1[0].items():  # [{<Atom 'O.'>: <GroupAtom [*3 'R']>}]
+            self.assertEqual(key.atomtype.label, 'O2s')
+            self.assertEqual(val.label, '*3')
+        for isomorphic_subgraph in isomorphic_subgraphs_2:
+            # [{<Atom 'C'>: <GroupAtom [*1 'R']>, <Atom 'H'>: <GroupAtom [*2 'H']>}, {<Atom 'C'>: <GroupAtom [*1 'R']>,
+            # <Atom 'H'>: <GroupAtom [*2 'H']>}, {<Atom 'C'>: <GroupAtom [*1 'R']>, <Atom 'H'>: <GroupAtom [*2 'H']>},
+            # {<Atom 'C'>: <GroupAtom [*1 'R']>, <Atom 'H'>: <GroupAtom [*2 'H']>}, {<Atom 'C'>: <GroupAtom [*1 'R']>,
+            # <Atom 'H'>: <GroupAtom [*2 'H']>}, {<Atom 'N'>: <GroupAtom [*1 'R']>, <Atom 'H'>: <GroupAtom [*2 'H']>},
+            # {<Atom 'N'>: <GroupAtom [*1 'R']>, <Atom 'H'>: <GroupAtom [*2 'H']>}]
+            for key, val in isomorphic_subgraph.items():
+                if key.is_hydrogen():
+                    self.assertEqual(val.label, '*2')
+                else:
+                    self.assertEqual(val.label, '*1')
+        isomorphic_subgraph = get_isomorphic_subgraph(isomorphic_subgraph_1=isomorphic_subgraphs_1[0],
+                                                      isomorphic_subgraph_2=isomorphic_subgraphs_2[0],
+                                                      mol_1=spc_1.mol,
+                                                      mol_2=spc_2.mol,
+                                                      )
+        self.assertEqual(isomorphic_subgraph, {0: '*3', 3: '*1', 5: '*2'})
+        isomorphic_subgraph = get_isomorphic_subgraph(isomorphic_subgraph_1=isomorphic_subgraphs_1[0],
+                                                      isomorphic_subgraph_2=isomorphic_subgraphs_2[2],
+                                                      mol_1=spc_1.mol,
+                                                      mol_2=spc_2.mol,
+                                                      )
+        self.assertEqual(isomorphic_subgraph, {0: '*3', 4: '*1', 7: '*2'})
+
+
+if __name__ == '__main__':
+    unittest.main(testRunner=unittest.TextTestRunner(verbosity=2))
diff --git a/arc/reaction.py b/arc/reaction/reaction.py
similarity index 85%
rename from arc/reaction.py
rename to arc/reaction/reaction.py
index 84fffc6b6c..7d499d3e15 100644
--- a/arc/reaction.py
+++ b/arc/reaction/reaction.py
@@ -5,12 +5,11 @@
 from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union
 
 from arkane.common import get_element_mass
-from rmgpy.reaction import Reaction
 from rmgpy.species import Species
 
-import arc.rmgdb as rmgdb
 from arc.common import get_logger
 from arc.exceptions import ReactionError, InputError
+from arc.reaction.family import ReactionFamily, get_reaction_family_products
 from arc.species.converter import (check_xyz_dict,
                                    sort_xyz_using_indices,
                                    translate_to_center_of_mass,
@@ -21,7 +20,7 @@
 from arc.species.species import ARCSpecies, check_atom_balance, check_label
 
 if TYPE_CHECKING:
-    from rmgpy.data.rmg import RMGDatabase
+    from rmgpy.molecule import Molecule
 
 
 logger = get_logger()
@@ -46,7 +45,10 @@ class ARCReaction(object):
         r_species (List[ARCSpecies], optional): A list of reactants :ref:`ARCSpecies <species>` objects.
         p_species (List[ARCSpecies], optional): A list of products :ref:`ARCSpecies <species>` objects.
         ts_label (str, optional): The :ref:`ARCSpecies <species>` label of the respective TS.
-        rmg_reaction (Reaction, optional): An RMG Reaction class.
+        rmg_family_set (Union[List[str], str], optional): The RMG family set to which the reaction belongs
+                                                          (corresponds to sets in db families recommended.py)
+                                                          or an explicit names of families to consider
+                                                          given as a list of strings.
         ts_xyz_guess (list, optional): A list of TS XYZ user guesses, each in a string format.
         xyz (list, optional): Identical to `ts_xyz_guess`, used as a shortcut.
         multiplicity (int, optional): The reaction surface multiplicity. A trivial guess will be made unless provided.
@@ -61,7 +63,7 @@ class ARCReaction(object):
     Attributes:
         label (str): The reaction's label in the format `r1 + r2 <=> p1 + p2`
                      (or unimolecular on either side, as appropriate).
-        family (KineticsFamily): The RMG kinetic family, if applicable.
+        family (str): The RMG kinetic family, if applicable.
         family_own_reverse (bool): Whether the RMG family is its own reverse.
         reactants (List[str]): A list of reactants labels corresponding to an :ref:`ARCSpecies <species>`.
         products (List[str]): A list of products labels corresponding to an :ref:`ARCSpecies <species>`.
@@ -71,7 +73,7 @@ class ARCReaction(object):
         dh_rxn298 (float): The heat of reaction at 298K.
         kinetics (Arrhenius): The high pressure limit rate coefficient calculated by ARC.
         rmg_kinetics (Arrhenius): The kinetics generated by RMG, for reality-check.
-        rmg_reaction (Reaction): An RMG Reaction class.
+        rmg_family_set (Union[List[str]]): The RMG family set or a list of specific families to consider.
         rmg_reactions (list): A list of RMG Reaction objects with RMG rates for comparisons.
         long_kinetic_description (str): A description for the species entry in the thermo library outputted.
         ts_xyz_guess (list): A list of TS XYZ user guesses, each in a string format.
@@ -94,7 +96,7 @@ def __init__(self,
                  r_species: Optional[List[ARCSpecies]] = None,
                  p_species: Optional[List[ARCSpecies]] = None,
                  ts_label: Optional[str] = None,
-                 rmg_reaction: Optional[Reaction] = None,
+                 rmg_family_set: Union[List[str]] = 'default',
                  ts_xyz_guess: Optional[list] = None,
                  xyz: Optional[list] = None,
                  multiplicity: Optional[int] = None,
@@ -109,9 +111,10 @@ def __init__(self,
         self.p_species = p_species or list()
         self.kinetics = None
         self.rmg_kinetics = None
+        self.rmg_family_set = rmg_family_set
         self.long_kinetic_description = ''
-        self.family = None
-        self.family_own_reverse = False
+        self._family = None
+        self._family_own_reverse = False
         self.ts_label = ts_label
         self.dh_rxn298 = None
         self.rmg_reactions = None
@@ -132,10 +135,8 @@ def __init__(self,
             self.reactants = [check_label(reactant)[0] for reactant in reactants] if reactants else list()
             products = products or [spc.label for spc in self.p_species] or None
             self.products = [check_label(product)[0] for product in products] if products else list()
-            self.rmg_reaction = rmg_reaction
-            if self.rmg_reaction is None and not self.label \
-                    and not (len(self.reactants) * len(self.products)) \
-                    and not (len(self.r_species) * len(self.p_species)):
+            if (not self.label and not (len(self.reactants) * len(self.products))
+                    and not (len(self.r_species) * len(self.p_species))):
                 raise InputError(f'Cannot determine reactants and/or products labels for reaction {self.label}')
             self.set_label_reactants_products()
             self.ts_xyz_guess = ts_xyz_guess or list()
@@ -145,7 +146,6 @@ def __init__(self,
                                 f'reactants and {len(self.products)} products for reaction {self.label}.')
         if not isinstance(self.ts_xyz_guess, list):
             self.ts_xyz_guess = [self.ts_xyz_guess]
-        self.arc_species_from_rmg_reaction()
         self.remove_dup_species()
         self.check_atom_balance()
 
@@ -175,9 +175,6 @@ def charge(self):
         if self._charge is None:
             if len(self.r_species):
                 self._charge = self.get_rxn_charge()
-            elif self.rmg_reaction is not None:
-                self._charge = sum([spc.molecule[0].get_net_charge() for spc in
-                                    self.rmg_reaction.reactants + self.rmg_reaction.products])
         return self._charge
 
     @charge.setter
@@ -203,11 +200,40 @@ def multiplicity(self, value):
                 raise InputError(f'Reaction multiplicity must be an integer, got {value} which is a {type(value)}.')
             logger.info(f'Setting multiplicity of reaction {self.label} to {self._multiplicity}')
 
+    @property
+    def family(self):
+        """The RMG reaction family"""
+        if self._family is None:
+            self._family, self._family_own_reverse = self.determine_family()
+        return self._family
+
+    @family.setter
+    def family(self, value):
+        """Allow setting family"""
+        self._family = value
+        if value is not None and not isinstance(value, str):
+            raise InputError(f'Reaction family must be a string, got {value} which is a {type(value)}.')
+
+    @property
+    def family_own_reverse(self):
+        """The RMG reaction family's own reverse property"""
+        if self._family_own_reverse is None:
+            self._family, self._family_own_reverse = self.determine_family()
+        return self._family_own_reverse
+
+    @family_own_reverse.setter
+    def family_own_reverse(self, value):
+        """Allow setting family_own_reverse"""
+        self._family_own_reverse = value
+        if value is not None and not isinstance(value, bool):
+            raise InputError(f'Reaction family_own_reverse must be a boolean, got {value} which is a {type(value)}.')
+
     def __str__(self) -> str:
         """Return a string representation of the object"""
         str_representation = f'ARCReaction('
         str_representation += f'label="{self.label}", '
-        str_representation += f'rmg_reaction="{self.rmg_reaction}", '
+        if self.family is not None:
+            str_representation += f'family="{self.family}", '
         if self.preserve_param_in_scan is not None:
             str_representation += f'preserve_param_in_scan="{self.preserve_param_in_scan}", '
         str_representation += f'multiplicity={self.multiplicity}, '
@@ -216,6 +242,7 @@ def __str__(self) -> str:
 
     def as_dict(self,
                 reset_atom_ids: bool = False,
+                report_family: bool = True,
                 ) -> dict:
         """
         A helper function for dumping this object as a dictionary in a YAML file for restarting ARC.
@@ -224,6 +251,7 @@ def as_dict(self,
             reset_atom_ids (bool, optional): Whether to reset the atom IDs in the .mol Molecule attribute of reactant
                                              and product species. Useful when copying the object to avoid duplicate
                                              atom IDs between different object instances.
+            report_family (bool, optional): Whether to report the reaction family.
 
         Returns:
             dict: The dictionary representation of the object instance.
@@ -247,12 +275,13 @@ def as_dict(self,
             reaction_dict['done_opt_r_n_p'] = self.done_opt_r_n_p
         if self.preserve_param_in_scan is not None:
             reaction_dict['preserve_param_in_scan'] = self.preserve_param_in_scan
-        if 'rmg_reaction' in reaction_dict:
-            reaction_dict['rmg_reaction'] = self.rmg_reaction_to_str()
-        if self.family is not None:
-            reaction_dict['family'] = self.family.label
-        if self.family_own_reverse:
-            reaction_dict['family_own_reverse'] = self.family_own_reverse
+        if 'rmg_family_set' in reaction_dict and reaction_dict['rmg_family_set'] != 'default':
+            reaction_dict['rmg_family_set'] = self.rmg_family_set
+        if report_family:
+            if self.family is not None:
+                reaction_dict['family'] = self.family
+            if self.family_own_reverse:
+                reaction_dict['family_own_reverse'] = self.family_own_reverse
         if self.long_kinetic_description:
             reaction_dict['long_kinetic_description'] = self.long_kinetic_description
         if len(self.ts_xyz_guess):
@@ -276,28 +305,12 @@ def from_dict(self,
         self.reactants = reaction_dict.get('reactants') or list()
         self.products = reaction_dict.get('products') or list()
         if 'family' in reaction_dict and reaction_dict['family'] is not None:
-            db = rmgdb.make_rmg_database_object()
-            rmgdb.load_families_only(db)
-            self.family = rmgdb.get_family(rmgdb=db, label=reaction_dict['family'])
-            self.family.save_order = True
-        else:
-            self.family = None
+            self.family = reaction_dict['family']
         self.family_own_reverse = reaction_dict['family_own_reverse'] if 'family_own_reverse' in reaction_dict else False
-        if 'rmg_reaction' in reaction_dict:
-            self.rmg_reaction_from_str(reaction_string=reaction_dict['rmg_reaction'])
-        else:
-            self.rmg_reaction = None
+        self.rmg_family_set = reaction_dict['rmg_family_set'] if 'rmg_family_set' in reaction_dict else 'default'
         self.set_label_reactants_products(species_list)
-        if self.rmg_reaction is None and not (len(self.reactants) * len(self.products)):
-            raise InputError(f'Cannot determine reactants and/or products labels for reaction {self.label}')
         if not (len(self.reactants) * len(self.products)):
-            if not all([spc.label for spc in self.rmg_reaction.reactants + self.rmg_reaction.products]):
-                raise InputError(f'All species in a reaction must be labeled (and the labels must correspond '
-                                 f'to respective Species in ARC). If an RMG Reaction object was passes, make '
-                                 f'sure that all species in the reactants and products are correctly labeled. '
-                                 f'Problematic reaction: {self.label}')
-            self.reactants = [check_label(spc.label)[0] for spc in self.rmg_reaction.reactants]
-            self.products = [check_label(spc.label)[0] for spc in self.rmg_reaction.products]
+            raise InputError(f'Cannot determine reactants and/or products labels for reaction {self.label}')
         if self.ts_label is None:
             self.ts_label = reaction_dict['ts_label'] if 'ts_label' in reaction_dict else None
         if species_list is not None and 'r_species' in reaction_dict and len(reaction_dict['r_species']) \
@@ -337,16 +350,18 @@ def copy(self):
         reaction_dict = self.as_dict(reset_atom_ids=True)
         return ARCReaction(reaction_dict=reaction_dict)
 
-    def flip_reaction(self):
+    def flip_reaction(self, report_family: bool = True):
         """
         Get a copy of this object instance with flipped reactants and products.
 
+        Args:
+            report_family (bool, optional): Whether to report the reaction family.
+
         Returns:
             ARCReaction: A copy of this object instance with flipped reactants and products.
         """
-        reaction_dict = self.as_dict(reset_atom_ids=True)
-        reset_keys = ['label', 'index', 'atom_map', 'rmg_reaction',
-                      'family', 'family_own_reverse', 'long_kinetic_description']
+        reaction_dict = self.as_dict(reset_atom_ids=True, report_family=report_family)
+        reset_keys = ['label', 'index', 'atom_map', 'family', 'family_own_reverse', 'long_kinetic_description']
         if 'r_species' in reaction_dict.keys() and 'p_species' in reaction_dict.keys():
             reaction_dict['r_species'], reaction_dict['p_species'] = reaction_dict['p_species'], reaction_dict['r_species']
         else:
@@ -362,7 +377,6 @@ def flip_reaction(self):
         reaction_dict['label'] = self.arrow.join([label_splits[1], label_splits[0]])
         flipped_rxn = ARCReaction(reaction_dict=reaction_dict)
         flipped_rxn.set_label_reactants_products()
-        flipped_rxn.rmg_reaction_from_arc_species()
         return flipped_rxn
 
     def is_isomerization(self):
@@ -407,9 +421,6 @@ def set_label_reactants_products(self, species_list: Optional[List[ARCSpecies]]
                     if not len(self.p_species) and len(self.products):
                         self.p_species = [spc for spc in species_list if spc.label in self.products
                                           or spc.original_label in self.products]
-            elif self.rmg_reaction is not None:
-                self.reactants = [r.label for r in self.rmg_reaction.reactants]
-                self.products = [p.label for p in self.rmg_reaction.products]
             elif len(self.r_species) and len(self.p_species):
                 self.reactants = [r.label for r in self.r_species]
                 self.products = [p.label for p in self.p_species]
@@ -420,12 +431,6 @@ def set_label_reactants_products(self, species_list: Optional[List[ARCSpecies]]
             elif len(self.r_species) and len(self.p_species):
                 self.label = self.arrow.join([self.plus.join(r.label for r in self.r_species),
                                               self.plus.join(p.label for p in self.p_species)])
-            elif self.rmg_reaction is not None:
-                # This will probably never be executed, but OK to keep.
-                self.label = self.arrow.join([self.plus.join(r.label for r in self.rmg_reaction.reactants),
-                                              self.plus.join(p.label for p in self.rmg_reaction.products)])
-        if self.rmg_reaction is None:
-            self.rmg_reaction_from_arc_species()
         elif not self.label and not (len(self.reactants) * len(self.products)):
             raise ReactionError('Either a label or reactants and products lists must be specified')
         self.reactants = [check_label(reactant)[0] for reactant in self.reactants]
@@ -434,51 +439,6 @@ def set_label_reactants_products(self, species_list: Optional[List[ARCSpecies]]
             raise ReactionError(f'Both the reactants and products must be specified for a reaction, '
                                 f'got: reactants = {self.reactants}, products = {self.products}.')
 
-    def rmg_reaction_to_str(self) -> str:
-        """A helper function for dumping the RMG Reaction object as a string for the YAML restart dictionary"""
-        return self.arrow.join([self.plus.join(r.molecule[0].copy(deep=True).to_smiles()
-                                               for r in self.rmg_reaction.reactants),
-                                self.plus.join(p.molecule[0].copy(deep=True).to_smiles()
-                                               for p in self.rmg_reaction.products)])
-
-    def rmg_reaction_from_str(self, reaction_string: str):
-        """A helper function for regenerating the RMG Reaction object from a string representation"""
-        reactants, products = reaction_string.split(self.arrow)
-        reactants = [Species(smiles=smiles) for smiles in reactants.split(self.plus)]
-        products = [Species(smiles=smiles) for smiles in products.split(self.plus)]
-        self.rmg_reaction = Reaction(reactants=reactants, products=products)
-
-    def rmg_reaction_from_arc_species(self):
-        """
-        A helper function for generating the RMG Reaction object from ARCSpecies
-        Used for determining the family.
-        """
-        if self.rmg_reaction is None and len(self.r_species) and len(self.p_species) and \
-                all([arc_spc.mol is not None for arc_spc in self.r_species + self.p_species]):
-            reactants, products = self.get_reactants_and_products(arc=False)  # Returns RMG Species.
-            self.rmg_reaction = Reaction(reactants=reactants, products=products)
-
-    def arc_species_from_rmg_reaction(self):
-        """
-        A helper function for generating the ARC Species (.r_species and .p_species) from the RMG Reaction object
-        """
-        if self.rmg_reaction is not None and not len(self.r_species) and not len(self.p_species):
-            self.r_species, self.p_species = list(), list()
-            for i, rmg_reactant in enumerate(self.rmg_reaction.reactants):
-                if len(self.reactants) > i:
-                    label = self.reactants[i]
-                else:
-                    label = rmg_reactant.label or rmg_reactant.molecule[0].copy(deep=True).to_smiles()
-                label = check_label(label)[0]
-                self.r_species.append(ARCSpecies(label=label, mol=rmg_reactant.molecule[0]))
-            for i, rmg_product in enumerate(self.rmg_reaction.products):
-                if len(self.products) > i:
-                    label = self.products[i]
-                else:
-                    label = rmg_product.label or rmg_product.molecule[0].copy(deep=True).to_smiles()
-                label = check_label(label)[0]
-                self.p_species.append(ARCSpecies(label=label, mol=rmg_product.molecule[0]))
-
     def get_rxn_charge(self):
         """A helper function for determining the surface charge"""
         if len(self.r_species):
@@ -551,31 +511,45 @@ def get_rxn_multiplicity(self):
         return multiplicity
 
     def determine_family(self,
-                         rmg_database: 'RMGDatabase',
-                         save_order: bool = True,
+                         consider_rmg_families: bool = True,
+                         consider_arc_families: bool = True,
+                         discover_own_reverse_rxns_in_reverse: bool = False,
                          ):
         """
-        Determine the RMG family.
+        Determine the RMG reaction family.
         Populates the .family, and .family_own_reverse attributes.
-        A wrapper for the rmgdb determine_reaction_family() function.
 
         Args:
-            rmg_database (RMGDatabase): The RMGDatabase object instance.
-            save_order (bool, optional): Whether to retain atomic order of the RMG ``reaction`` object instance.
-        """
-        if self.rmg_reaction is None:
-            self.rmg_reaction_from_arc_species()
-        if self.rmg_reaction is not None:
-            self.family, self.family_own_reverse = rmgdb.determine_reaction_family(rmgdb=rmg_database,
-                                                                                   reaction=self.rmg_reaction.copy(),
-                                                                                   save_order=save_order,
-                                                                                   )
-            if self.family is None:
-                flipped_rmg_reaction = self.flip_reaction().rmg_reaction
-                self.family, self.family_own_reverse = rmgdb.determine_reaction_family(rmgdb=rmg_database,
-                                                                                       reaction=flipped_rmg_reaction,
-                                                                                       save_order=save_order,
-                                                                                       )
+            consider_rmg_families (bool, optional): Whether to consider RMG's families in addition to ARC's.
+            consider_arc_families (bool, optional): Whether to consider ARC's families in addition to RMG's.
+            discover_own_reverse_rxns_in_reverse (bool, optional): Whether to discover own reverse reactions in reverse.
+        """
+        product_dicts = get_reaction_family_products(rxn=self,
+                                                     rmg_family_set=self.rmg_family_set,
+                                                     consider_rmg_families=consider_rmg_families,
+                                                     consider_arc_families=consider_arc_families,
+                                                     discover_own_reverse_rxns_in_reverse=discover_own_reverse_rxns_in_reverse,
+                                                     )
+        if len(product_dicts):
+            family, family_own_reverse = product_dicts[0]['family'], product_dicts[0]['own_reverse']
+            return family, family_own_reverse
+        return None, None
+
+    def get_family_products(self) -> Optional[List['Molecule']]:
+        """
+        Determine the RMG reaction family.
+        Populates the .family, and .family_own_reverse attributes.
+
+        Returns:
+            Optional[List[Molecule]]: The products of the reaction with the same atom order as the reactants,
+            generated by the family. Currently only returning the first product list.
+        """
+        product_dicts = get_reaction_family_products(rxn=self,
+                                                     rmg_family_set=[self.family],
+                                                     )
+        if len(product_dicts):
+            return product_dicts[0]['products']
+        return None
 
     def check_attributes(self):
         """Check that the Reaction object is defined correctly"""
@@ -817,12 +791,12 @@ def get_expected_changing_bonds(self,
         """
         if self.family is None:
             return None, None
-        template_recipe_actions = self.family.forward_recipe.actions
+        family = ReactionFamily(label=self.family)
         # E.g.: [['BREAK_BOND', '*1', 1, '*2'], ['FORM_BOND', '*2', 1, '*3'], ['GAIN_RADICAL', '*1', '1']]
         expected_breaking_bonds = [tuple(sorted([r_label_dict[action[1]], r_label_dict[action[3]]]))
-                                   for action in template_recipe_actions if action[0] == 'BREAK_BOND']
+                                   for action in family.actions if action[0] == 'BREAK_BOND']
         expected_forming_bonds = [tuple(sorted([r_label_dict[action[1]], r_label_dict[action[3]]]))
-                                  for action in template_recipe_actions if action[0] == 'FORM_BOND']
+                                  for action in family.actions if action[0] == 'FORM_BOND']
         return expected_breaking_bonds, expected_forming_bonds
 
     def get_number_of_atoms_in_reaction_zone(self) -> Optional[int]:
@@ -834,10 +808,10 @@ def get_number_of_atoms_in_reaction_zone(self) -> Optional[int]:
         """
         if self.family is None:
             return None
-        template_recipe_actions = self.family.forward_recipe.actions
+        family = ReactionFamily(label=self.family)
         # E.g.: [['BREAK_BOND', '*1', 1, '*2'], ['FORM_BOND', '*2', 1, '*3'], ['GAIN_RADICAL', '*1', '1']
         labels = list()
-        for action in template_recipe_actions:
+        for action in family.actions:
             for entry in action:
                 if isinstance(entry, str) and '*' in entry:
                     labels.append(entry)
diff --git a/arc/reaction_test.py b/arc/reaction/reaction_test.py
similarity index 95%
rename from arc/reaction_test.py
rename to arc/reaction/reaction_test.py
index 5c3b85e7fc..7dd088715b 100644
--- a/arc/reaction_test.py
+++ b/arc/reaction/reaction_test.py
@@ -2,7 +2,7 @@
 # encoding: utf-8
 
 """
-This module contains unit tests of the arc.reaction module
+This module contains unit tests of the arc.reaction.reaction module
 """
 
 from itertools import permutations
@@ -13,11 +13,10 @@
 from rmgpy.reaction import Reaction
 from rmgpy.species import Species
 
-import arc.rmgdb as rmgdb
 from arc.common import ARC_PATH, almost_equal_lists, read_yaml_file
 from arc.exceptions import ReactionError
 from arc.main import ARC
-from arc.reaction import ARCReaction, remove_dup_species
+from arc.reaction.reaction import ARCReaction, remove_dup_species
 from arc.scheduler import Scheduler
 from arc.species import ARCSpecies
 from arc.mapping.engine import check_atom_map, label_species_atoms
@@ -34,10 +33,7 @@ def setUpClass(cls):
         A method that is run before all unit tests in this class.
         """
         cls.maxDiff = None
-        cls.rmgdb = rmgdb.make_rmg_database_object()
-        cls.rmgdb.kinetics.families = None
-        rmgdb.load_families_only(cls.rmgdb, "all")
-        
+
         cls.h2_xyz = {'coords': ((0, 0, 0.3736550), (0, 0, -0.3736550)), 'isotopes': (1, 1), 'symbols': ('H', 'H')}
         cls.o2_xyz = {'coords': ((0, 0, 0.6487420), (0, 0, -0.6487420)), 'isotopes': (16, 16), 'symbols': ('O', 'O')}
         cls.co_xyz = {'coords': ((0, 0, -0.6748240), (0, 0, 0.5061180)), 'isotopes': (12, 16), 'symbols': ('C', 'O')}
@@ -99,24 +95,14 @@ def setUpClass(cls):
                                H                 -0.36439762   -1.57761595   -0.41622918
                                H                 -1.43807526    1.62776079    0.73816131
                                H                 -1.28677889    1.04716138   -1.01532486"""
-        cls.rxn1 = ARCReaction(reactants=['CH4', 'OH'], products=['CH3', 'H2O'],
-                               rmg_reaction=Reaction(reactants=[Species(label='CH4', smiles='C'),
-                                                                Species(label='OH', smiles='[OH]')],
-                                                     products=[Species(label='CH3', smiles='[CH3]'),
-                                                               Species(label='H2O', smiles='O')]))
-        cls.rxn2 = ARCReaction(reactants=['C2H5', 'OH'], products=['C2H4', 'H2O'],
-                               rmg_reaction=Reaction(reactants=[Species(label='C2H5', smiles='C[CH2]'),
-                                                                Species(label='OH', smiles='[OH]')],
-                                                     products=[Species(label='C2H4', smiles='C=C'),
-                                                               Species(label='H2O', smiles='O')]))
-        cls.rxn3 = ARCReaction(reactants=['CH3CH2NH'], products=['CH2CH2NH2'],
-                               rmg_reaction=Reaction(reactants=[Species(label='CH3CH2NH', smiles='CC[NH]')],
-                                                     products=[Species(label='CH2CH2NH2', smiles='[CH2]CN')]))
-        cls.rxn4 = ARCReaction(reactants=['NH2', 'NH2NH'], products=['N', 'NH2N'],
-                               rmg_reaction=Reaction(reactants=[Species(label='NH2', smiles='[NH2]'),
-                                                                Species(label='NH2NH', smiles='N[NH]')],
-                                                     products=[Species(label='N', smiles='N'),
-                                                               Species(label='NH2N', smiles='N[N]')]))
+        cls.rxn1 = ARCReaction(r_species=[ARCSpecies(label='CH4', smiles='C'), ARCSpecies(label='OH', smiles='[OH]')],
+                               p_species=[ARCSpecies(label='CH3', smiles='[CH3]'), ARCSpecies(label='H2O', smiles='O')])
+        cls.rxn2 = ARCReaction(r_species=[ARCSpecies(label='C2H5', smiles='C[CH2]'), ARCSpecies(label='OH', smiles='[OH]')],
+                               p_species=[ARCSpecies(label='C=C', smiles='C2H4'), ARCSpecies(label='H2O', smiles='O')])
+        cls.rxn3 = ARCReaction(r_species=[ARCSpecies(label='CC[NH]', smiles='CH3CH2NH')],
+                               p_species=[ARCSpecies(label='[CH2]CH', smiles='CH2CH2NH2')])
+        cls.rxn4 = ARCReaction(r_species=[ARCSpecies(label='NH2', smiles='[NH2]'), ARCSpecies(label='N[NH]', smiles='NH2NH')],
+                               p_species=[ARCSpecies(label='NH3', smiles='N'), ARCSpecies(label='N[N]', smiles='NH2N')])
         cls.rxn5 = ARCReaction(reactants=['NH2', 'NH2'], products=['NH', 'NH3'],
                                r_species=[ARCSpecies(label='NH2', smiles='[NH2]')],
                                p_species=[ARCSpecies(label='NH', smiles='[NH]'),
@@ -146,10 +132,10 @@ def setUpClass(cls):
         cls.rxn9 = ARCReaction(r_species=[ARCSpecies(label='NCOO', smiles='NCO[O]')],
                                p_species=[ARCSpecies(label='NHCH2', smiles='N=C'),
                                           ARCSpecies(label='HO2', smiles='O[O]')])
-        cls.rxn10 = ARCReaction(rmg_reaction=Reaction(reactants=[Species(label='HNO', smiles='N=O'),
-                                                                 Species(label='NO2', smiles='O=[N+][O-]')],
-                                                      products=[Species(label='HNO2', smiles='[O-][NH+]=O'),
-                                                                Species(label='NO', smiles='[N]=O')]))
+        cls.rxn10 = ARCReaction(r_species=[ARCSpecies(label='HNO', smiles='N=O'),
+                                           ARCSpecies(label='NO2', smiles='O=[N+][O-]')],
+                                p_species=[ARCSpecies(label='HNO2', smiles='[O-][NH+]=O'),
+                                           ARCSpecies(label='NO', smiles='[N]=O')])
         cls.rxn11 = ARCReaction(r_species=[ARCSpecies(label='C[CH]C', smiles='C[CH]C', xyz=cls.ch3chch3_xyz)],
                                 p_species=[ARCSpecies(label='[CH2]CC', smiles='[CH2]CC', xyz=cls.ch3ch2ch2_xyz)])
 
@@ -164,7 +150,6 @@ def test_str(self):
 
     def test_as_dict(self):
         """Test ARCReaction.as_dict()"""
-        self.rxn1.determine_family(self.rmgdb)
         rxn_dict_1 = self.rxn1.as_dict()
         # mol.atoms are not tested since all id's (including connectivity) changes depending on how the test is run.
         expected_dict_1 = {'family': 'H_Abstraction',
@@ -229,6 +214,7 @@ def test_as_dict(self):
         rxn_dict_6 = self.rxn6.as_dict()
         # The ``long_thermo_description`` attribute isn't deterministic (order could change)
         expected_dict_6 = {'label': 'NH2 + N2H3 <=> NH3 + H2NN[S]',
+                           'family': 'Disproportionation',
                            'multiplicity': 1,
                            'p_species': [{'bond_corrections': {'H-N': 3},
                                           'cheap_conformer': 'N       0.00064924   -0.00099698    0.29559292\n'
@@ -300,7 +286,7 @@ def test_from_dict(self):
         self.assertEqual(rxn.label, 'CH4 + OH <=> CH3 + H2O')
         self.assertEqual(rxn.multiplicity, 2)
         self.assertEqual(rxn.charge, 0)
-        self.assertEqual(rxn.family.label, 'H_Abstraction')
+        self.assertEqual(rxn.family, 'H_Abstraction')
         self.assertEqual(rxn.family_own_reverse, True)
         self.assertEqual(rxn.reactants, ['CH4', 'OH'])
         self.assertEqual(rxn.products, ['CH3', 'H2O'])
@@ -372,65 +358,32 @@ def test_is_isomerization(self):
         self.assertFalse(self.rxn8.is_isomerization())
         self.assertFalse(self.rxn9.is_isomerization())
 
-    def test_from_rmg_reaction(self):
-        """Test setting up an ARCReaction from an RMG Reaction"""
-        rmg_rxn_1 = Reaction(reactants=[Species(label='nC3H7', smiles='[CH2]CC')],
-                             products=[Species(label='iC3H7', smiles='C[CH]C')])
-        rxn_1 = ARCReaction(rmg_reaction=rmg_rxn_1)
-        self.assertEqual(rxn_1.label, 'nC3H7 <=> iC3H7')
-
-        rmg_rxn_2 = Reaction(reactants=[Species(label='OH', smiles='[OH]'), Species(label='OH', smiles='[OH]')],
-                             products=[Species(label='O', smiles='[O]'), Species(label='H2O', smiles='O')])
-        rxn_2 = ARCReaction(rmg_reaction=rmg_rxn_2)
-        self.assertEqual(rxn_2.label, 'OH + OH <=> O + H2O')
-
-    def test_rmg_reaction_to_str(self):
-        """Test the rmg_reaction_to_str() method and the reaction label generated"""
-        spc1 = Species().from_smiles('CON=O')
-        spc1.label = 'CONO'
-        spc2 = Species().from_smiles('C[N+](=O)[O-]')
-        spc2.label = 'CNO2'
-        rmg_reaction = Reaction(reactants=[spc1], products=[spc2])
-        rxn = ARCReaction(rmg_reaction=rmg_reaction)
-        rxn_str = rxn.rmg_reaction_to_str()
-        self.assertEqual(rxn_str, 'CON=O <=> [O-][N+](=O)C')
-        self.assertEqual(rxn.label, 'CONO <=> CNO2')
-
     def test_rxn_family(self):
         """Test that ARC gets the correct RMG family for different reactions"""
-        self.rxn1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(self.rxn1.family.label, 'H_Abstraction')
+        self.assertEqual(self.rxn1.family, 'H_Abstraction')
         self.assertTrue(self.rxn1.family_own_reverse)
-        self.rxn2.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(self.rxn2.family.label, 'Disproportionation')
+        self.assertEqual(self.rxn2.family, 'Disproportionation')
         self.assertFalse(self.rxn2.family_own_reverse)
-        self.rxn3.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(self.rxn3.family.label, 'intra_H_migration')
+        self.assertEqual(self.rxn3.family, 'intra_H_migration')
         self.assertTrue(self.rxn3.family_own_reverse)
-        self.rxn4.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(self.rxn4.family.label, 'H_Abstraction')
+        self.assertEqual(self.rxn4.family, 'H_Abstraction')
         self.rxn5.rmg_reaction_from_arc_species()
         self.rxn5.check_attributes()
-        self.rxn5.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(self.rxn5.family.label, 'H_Abstraction')
+        self.assertEqual(self.rxn5.family, 'H_Abstraction')
         self.rxn9.rmg_reaction_from_arc_species()
         self.rxn9.check_attributes()
-        self.rxn9.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(self.rxn9.family.label, 'HO2_Elimination_from_PeroxyRadical')
+        self.assertEqual(self.rxn9.family, 'HO2_Elimination_from_PeroxyRadical')
         rxn_9_flipped = self.rxn9.flip_reaction()
         rxn_9_flipped.rmg_reaction_from_arc_species()
         rxn_9_flipped.check_attributes()
-        rxn_9_flipped.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn_9_flipped.family.label, 'HO2_Elimination_from_PeroxyRadical')
-        self.rxn10.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(self.rxn10.family.label, 'H_Abstraction')
+        self.assertEqual(rxn_9_flipped.family, 'HO2_Elimination_from_PeroxyRadical')
+        self.assertEqual(self.rxn10.family, 'H_Abstraction')
         rxn_1 = ARCReaction(r_species=[ARCSpecies(label='C2H6', smiles='CC'),
                                        ARCSpecies(label='CCOOj', smiles='CCO[O]')],
                             p_species=[ARCSpecies(label='CCOOH', smiles='CCOO'),
                                        ARCSpecies(label='C2H5', smiles='C[CH2]')])
         rxn_1.check_attributes()
-        rxn_1.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn_1.family.label, 'H_Abstraction')
+        self.assertEqual(rxn_1.family, 'H_Abstraction')
 
         # Test identifying the reaction family for with zwitterions read from Arkane YAML files
         base_path = os.path.join(ARC_PATH, 'arc', 'testing', 'yml_testing', 'HNNO+NH3O=H2NO+NH2NO')
@@ -438,8 +391,7 @@ def test_rxn_family(self):
                                       ARCSpecies(label='NH3O', smiles='[O-][NH3+]', yml_path=os.path.join(base_path, 'NH3O.yml'))],
                            p_species=[ARCSpecies(label='H2NO', smiles='N[O]', yml_path=os.path.join(base_path, 'H2NO.yml')),
                                       ARCSpecies(label='NH2NO', smiles='NN=O', yml_path=os.path.join(base_path, 'NH2NO.yml'))])
-        rxn2.determine_family(rmg_database=self.rmgdb)
-        self.assertEqual(rxn2.family.label, 'H_Abstraction')
+        self.assertEqual(rxn2.family, 'H_Abstraction')
 
     def test_charge_property(self):
         """Test determining charge"""
@@ -448,7 +400,6 @@ def test_charge_property(self):
     def test_multiplicity_property(self):
         """Test determining multiplicity"""
         self.assertEqual(self.rxn1.multiplicity, 2)
-        self.rxn2.arc_species_from_rmg_reaction()
         self.assertEqual(self.rxn2.multiplicity, 1)
         self.assertEqual(self.rxn3.multiplicity, 2)
         self.assertEqual(self.rxn4.multiplicity, 3)
@@ -578,7 +529,6 @@ def test_get_species_count(self):
 
     def test_get_reactants_and_products(self):
         """Test getting reactants and products"""
-        self.rxn1.arc_species_from_rmg_reaction()
         self.rxn1.remove_dup_species()
         reactants, products = self.rxn1.get_reactants_and_products(arc=True)
         for spc in reactants + products:
@@ -621,7 +571,6 @@ def test_get_reactants_and_products(self):
 
     def test_get_expected_changing_bonds(self):
         """Test the get_expected_changing_bonds() method."""
-        self.rxn11.determine_family(self.rmgdb)
         expected_breaking_bonds, expected_forming_bonds = self.rxn11.get_expected_changing_bonds(
             r_label_dict={'*1': 1, '*2': 2, '*3': 6})
         self.assertEqual(expected_breaking_bonds, [(2, 6)])
@@ -629,10 +578,6 @@ def test_get_expected_changing_bonds(self):
 
     def test_get_number_of_atoms_in_reaction_zone(self):
         """Test the get_number_of_atoms_in_reaction_zone() method."""
-        for rxn in [self.rxn1, self.rxn2, self.rxn3, self.rxn4, self.rxn5, self.rxn6, self.rxn7, self.rxn8,
-                    self.rxn9, self.rxn10, self.rxn11]:
-            if rxn.family is None:
-                rxn.determine_family(self.rmgdb)
         self.assertEqual(self.rxn1.get_number_of_atoms_in_reaction_zone(), 3)  # H_Abstraction
         self.assertEqual(self.rxn2.get_number_of_atoms_in_reaction_zone(), 4)  # Disprop
         self.assertEqual(self.rxn3.get_number_of_atoms_in_reaction_zone(), 3)
@@ -693,8 +638,7 @@ def test_get_atom_map(self):
         p_2 = ARCSpecies(label='CH2NH2', smiles='[CH2]N', xyz=ch2nh2_xyz)
         rxn_3 = ARCReaction(reactants=['H', 'CH3NH2'], products=['H2', 'CH2NH2'],
                             r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn_3.determine_family(self.rmgdb)
-        self.assertEqual(rxn_3.family.label.lower(), "H_Abstraction".lower())
+        self.assertEqual(rxn_3.family, "H_Abstraction")
         self.assertIn(rxn_3.atom_map[0], [0, 1])
         self.assertEqual(rxn_3.atom_map[1:3], [2, 5])
         for index in [3, 4, 5]:
@@ -774,7 +718,6 @@ def test_get_atom_map(self):
         p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=c3h5o_xyz)
         p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=c4h10o_xyz)
         rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        rxn.determine_family(self.rmgdb)
         atom_map = rxn.atom_map
         self.assertEqual(atom_map[0:4], [0, 1, 3, 4])
         self.assertIn(atom_map[4], [5,6, 7])
@@ -1570,7 +1513,6 @@ def test_get_atom_map(self):
         rxn = ARCReaction(r_species=[ARCSpecies(label="r", smiles = 'C=C[CH]CC[CH]C=C')],
                           p_species=[ARCSpecies(label="p1", smiles= 'C=CC=C'),
                                      ARCSpecies(label="p2", smiles= 'C=CC=C')])
-        rxn.determine_family(rmg_database=self.rmgdb)
         c_symmetry_h_1 = [1, 2, 11, 12]            # symmetry of carbons with one hydrogen
         c_symmetry_h_2 = [0, 3, 10, 13]            # symmetry of carbons with two hydrogens
         h_symmetry1 = [6, 7, 16, 17]               # symmetry of hydrogens with one other hydrogen second order neighbor
@@ -1599,9 +1541,8 @@ def test_mapping_XY_elimination_hydroxyl(self):
                           p_species=[ARCSpecies(label="p1", smiles='C=C'),
                                      ARCSpecies(label="p2", smiles="F"),
                                      ARCSpecies(label="p3", smiles="O=C=O")])
-        rxn.determine_family(rmg_database=self.rmgdb)
-        if not rxn.family: # reaction family not found for some reason.
-            rxn.family = self.rmgdb.kinetics.families["XY_elimination_hydroxyl"]
+        # if not rxn.family:  # reaction family not found for some reason.
+        #     rxn.family = "XY_elimination_hydroxyl"
         atom_map = rxn.atom_map
         self.assertIsNotNone(rxn.family)
         self.assertTrue(check_atom_map(rxn=rxn))
diff --git a/arc/reaction/reaction_test.py~HEAD b/arc/reaction/reaction_test.py~HEAD
new file mode 100644
index 0000000000..73dbc01b51
--- /dev/null
+++ b/arc/reaction/reaction_test.py~HEAD
@@ -0,0 +1,1939 @@
+#!/usr/bin/env python3
+# encoding: utf-8
+
+"""
+This module contains unit tests of the arc.reaction.reaction module
+"""
+
+from itertools import permutations
+import os
+import shutil
+import unittest
+
+from rmgpy.reaction import Reaction
+from rmgpy.species import Species
+
+from arc.common import ARC_PATH, almost_equal_lists, read_yaml_file
+from arc.exceptions import ReactionError
+from arc.main import ARC
+from arc.reaction.reaction import ARCReaction, remove_dup_species
+from arc.scheduler import Scheduler
+from arc.species import ARCSpecies
+from arc.mapping.engine import check_atom_map, label_species_atoms
+
+
+class TestARCReaction(unittest.TestCase):
+    """
+    Contains unit tests for the ARCSpecies class
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """
+        A method that is run before all unit tests in this class.
+        """
+        cls.maxDiff = None
+
+        cls.h2_xyz = {'coords': ((0, 0, 0.3736550), (0, 0, -0.3736550)), 'isotopes': (1, 1), 'symbols': ('H', 'H')}
+        cls.o2_xyz = {'coords': ((0, 0, 0.6487420), (0, 0, -0.6487420)), 'isotopes': (16, 16), 'symbols': ('O', 'O')}
+        cls.co_xyz = {'coords': ((0, 0, -0.6748240), (0, 0, 0.5061180)), 'isotopes': (12, 16), 'symbols': ('C', 'O')}
+        cls.ho2_xyz = {'coords': ((0.0558910, -0.6204870, 0.0000000),
+                                  (0.0558910, 0.7272050, 0.0000000),
+                                  (-0.8942590, -0.8537420, 0.0000000)),
+                       'isotopes': (16, 16, 1), 'symbols': ('O', 'O', 'H')}
+        cls.ch2_xyz = {'coords': ((-1.3519460059345912e-10, -5.04203763365717e-10, 0.0),
+                                  (-1.064874800478917, -0.016329711355091817, 0.0),
+                                  (1.0648748006141107, 0.016329711859301474, 0.0)),
+                       'isotopes': (12, 1, 1), 'symbols': ('C', 'H', 'H')}
+        cls.nh_xyz = {'coords': ((0.509499983131626, 0.0, 0.0), (-0.509499983131626, 0.0, 0.0)),
+                      'isotopes': (14, 1), 'symbols': ('N', 'H')}
+        cls.ch2choh_xyz = """C      -0.80601307   -0.11773769    0.32792128
+                             C       0.23096883    0.47536513   -0.26437348
+                             O       1.44620485   -0.11266560   -0.46339257
+                             H      -1.74308628    0.41660480    0.45016601
+                             H      -0.75733964   -1.13345488    0.70278513
+                             H       0.21145717    1.48838416   -0.64841675
+                             H       1.41780836   -1.01649567   -0.10468897"""
+        cls.ch3cho_xyz = """C      -0.64851652   -0.03628781   -0.04007233
+                            C       0.84413281    0.04088405    0.05352862
+                            O       1.47323666   -0.23917853    1.06850992
+                            H      -1.06033881    0.94648764   -0.28238370
+                            H      -0.92134271   -0.74783968   -0.82281679
+                            H      -1.04996634   -0.37234114    0.91874740
+                            H       1.36260637    0.37153887   -0.86221771"""
+        cls.ch4_xyz = """C      -0.00000000    0.00000000    0.00000000
+                         H      -0.65055201   -0.77428020   -0.41251879
+                         H      -0.34927558    0.98159583   -0.32768232
+                         H      -0.02233792   -0.04887375    1.09087665
+                         H       1.02216551   -0.15844188   -0.35067554"""
+        cls.oh_xyz = """O       0.48890387    0.00000000    0.00000000
+                        H      -0.48890387    0.00000000    0.00000000"""
+        cls.ch3_xyz = """C       0.00000000    0.00000001   -0.00000000
+                         H       1.06690511   -0.17519582    0.05416493
+                         H      -0.68531716   -0.83753536   -0.02808565
+                         H      -0.38158795    1.01273118   -0.02607927"""
+        cls.h2o_xyz = """O      -0.00032832    0.39781490    0.00000000
+                         H      -0.76330345   -0.19953755    0.00000000
+                         H       0.76363177   -0.19827735    0.00000000"""
+        cls.ch3chch3_xyz = """C                  0.50180491   -0.93942231   -0.57086745
+                              C                  0.01278145    0.13148427    0.42191407
+                              C                 -0.86874485    1.29377369   -0.07163907
+                              H                  0.28549447    0.06799101    1.45462711
+                              H                  1.44553946   -1.32386345   -0.24456986
+                              H                  0.61096295   -0.50262210   -1.54153222
+                              H                 -0.24653265    2.11136864   -0.37045418
+                              H                 -0.21131163   -1.73585284   -0.61629002
+                              H                 -1.51770930    1.60958621    0.71830245
+                              H                 -1.45448167    0.96793094   -0.90568876"""
+        cls.ch3ch2ch2_xyz = """C                  0.48818717   -0.94549701   -0.55196729
+                               C                  0.35993708    0.29146456    0.35637075
+                               C                 -0.91834764    1.06777042   -0.01096751
+                               H                  0.30640232   -0.02058840    1.37845537
+                               H                  1.37634603   -1.48487836   -0.29673876
+                               H                  0.54172192   -0.63344406   -1.57405191
+                               H                  1.21252186    0.92358349    0.22063264
+                               H                 -0.36439762   -1.57761595   -0.41622918
+                               H                 -1.43807526    1.62776079    0.73816131
+                               H                 -1.28677889    1.04716138   -1.01532486"""
+        cls.rxn1 = ARCReaction(r_species=[ARCSpecies(label='CH4', smiles='C'), ARCSpecies(label='OH', smiles='[OH]')],
+                               p_species=[ARCSpecies(label='CH3', smiles='[CH3]'), ARCSpecies(label='H2O', smiles='O')])
+        cls.rxn2 = ARCReaction(r_species=[ARCSpecies(label='C2H5', smiles='C[CH2]'), ARCSpecies(label='OH', smiles='[OH]')],
+                               p_species=[ARCSpecies(label='C=C', smiles='C2H4'), ARCSpecies(label='H2O', smiles='O')])
+        cls.rxn3 = ARCReaction(r_species=[ARCSpecies(label='CC[NH]', smiles='CH3CH2NH')],
+                               p_species=[ARCSpecies(label='[CH2]CH', smiles='CH2CH2NH2')])
+        cls.rxn4 = ARCReaction(r_species=[ARCSpecies(label='NH2', smiles='[NH2]'), ARCSpecies(label='N[NH]', smiles='NH2NH')],
+                               p_species=[ARCSpecies(label='NH3', smiles='N'), ARCSpecies(label='N[N]', smiles='NH2N')])
+        cls.rxn5 = ARCReaction(reactants=['NH2', 'NH2'], products=['NH', 'NH3'],
+                               r_species=[ARCSpecies(label='NH2', smiles='[NH2]')],
+                               p_species=[ARCSpecies(label='NH', smiles='[NH]'),
+                                          ARCSpecies(label='NH3', smiles='N')])
+        cls.rxn6 = ARCReaction(reactants=['NH2', 'N2H3'], products=['NH3', 'H2NN(S)'],
+                               r_species=[ARCSpecies(label='NH2', smiles='[NH2]'),
+                                          ARCSpecies(label='N2H3', smiles='N[NH]')],
+                               p_species=[ARCSpecies(label='NH3', smiles='N'),
+                                          ARCSpecies(label='H2NN(S)', adjlist="""multiplicity 1
+                                                                                 1 N u0 p0 c+1 {2,D} {3,S} {4,S}
+                                                                                 2 N u0 p2 c-1 {1,D}
+                                                                                 3 H u0 p0 c0 {1,S}
+                                                                                 4 H u0 p0 c0 {1,S}""")])
+        cls.rxn7 = ARCReaction(reactants=['NH2', 'N2H3'], products=['NH3', 'H2NN(T)'],
+                               r_species=[ARCSpecies(label='NH2', smiles='[NH2]'),
+                                          ARCSpecies(label='N2H3', smiles='N[NH]')],
+                               p_species=[ARCSpecies(label='NH3', smiles='N'),
+                                          ARCSpecies(label='H2NN(T)', adjlist="""multiplicity 3
+                                                                                 1 N u0 p1 c0 {2,S} {3,S} {4,S}
+                                                                                 2 N u2 p1 c0 {1,S}
+                                                                                 3 H u0 p0 c0 {1,S}
+                                                                                 4 H u0 p0 c0 {1,S}""")])
+        cls.rxn8 = ARCReaction(r_species=[ARCSpecies(label='CH4', smiles='C', xyz=cls.ch4_xyz),
+                                          ARCSpecies(label='OH', smiles='[OH]', xyz=cls.oh_xyz)],
+                               p_species=[ARCSpecies(label='CH3', smiles='[CH3]', xyz=cls.ch3_xyz),
+                                          ARCSpecies(label='H2O', smiles='O', xyz=cls.h2o_xyz)])
+        cls.rxn9 = ARCReaction(r_species=[ARCSpecies(label='NCOO', smiles='NCO[O]')],
+                               p_species=[ARCSpecies(label='NHCH2', smiles='N=C'),
+                                          ARCSpecies(label='HO2', smiles='O[O]')])
+        cls.rxn10 = ARCReaction(r_species=[ARCSpecies(label='HNO', smiles='N=O'),
+                                           ARCSpecies(label='NO2', smiles='O=[N+][O-]')],
+                                p_species=[ARCSpecies(label='HNO2', smiles='[O-][NH+]=O'),
+                                           ARCSpecies(label='NO', smiles='[N]=O')])
+        cls.rxn11 = ARCReaction(r_species=[ARCSpecies(label='C[CH]C', smiles='C[CH]C', xyz=cls.ch3chch3_xyz)],
+                                p_species=[ARCSpecies(label='[CH2]CC', smiles='[CH2]CC', xyz=cls.ch3ch2ch2_xyz)])
+
+    def test_str(self):
+        """Test the string representation of the object"""
+        str_representation = str(self.rxn1)
+        self.assertEqual(self.rxn1.charge, 0)
+        expected_representation = 'ARCReaction(label="CH4 + OH <=> CH3 + H2O", ' \
+                                  'rmg_reaction="CH4 + OH <=> CH3 + H2O", ' \
+                                  'multiplicity=2, charge=0)'
+        self.assertEqual(str_representation, expected_representation)
+
+    def test_as_dict(self):
+        """Test ARCReaction.as_dict()"""
+        rxn_dict_1 = self.rxn1.as_dict()
+        # mol.atoms are not tested since all id's (including connectivity) changes depending on how the test is run.
+        expected_dict_1 = {'family': 'H_Abstraction',
+                           'family_own_reverse': True,
+                           'label': 'CH4 + OH <=> CH3 + H2O',
+                           'multiplicity': 2,
+                           'p_species': [{'bond_corrections': {'C-H': 3},
+                                          'cheap_conformer': 'C       0.00000000    0.00000001   -0.00000000\n'
+                                                             'H       1.06690511   -0.17519582    0.05416493\n'
+                                                             'H      -0.68531716   -0.83753536   -0.02808565\n'
+                                                             'H      -0.38158795    1.01273118   -0.02607927',
+                                          'label': 'CH3',
+                                          'long_thermo_description': "Bond corrections: {'C-H': 3}\n",
+                                          'mol': {'atom_order': rxn_dict_1['p_species'][0]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_1['p_species'][0]['mol']['atoms'],
+                                                  'multiplicity': 2,
+                                                  'props': {}},
+                                          'multiplicity': 2,
+                                          'number_of_rotors': 0},
+                                         {'bond_corrections': {'H-O': 2},
+                                          'cheap_conformer': 'O      -0.00032832    0.39781490    0.00000000\n'
+                                                             'H      -0.76330345   -0.19953755    0.00000000\n'
+                                                             'H       0.76363177   -0.19827735    0.00000000',
+                                          'label': 'H2O',
+                                          'long_thermo_description': "Bond corrections: {'H-O': 2}\n",
+                                          'mol': {'atom_order': rxn_dict_1['p_species'][1]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_1['p_species'][1]['mol']['atoms'],
+                                                  'multiplicity': 1,
+                                                  'props': {}},
+                                          'multiplicity': 1,
+                                          'number_of_rotors': 0}],
+                           'products': ['CH3', 'H2O'],
+                           'r_species': [{'bond_corrections': {'C-H': 4},
+                                          'cheap_conformer': 'C      -0.00000000   -0.00000000    0.00000000\n'
+                                                             'H      -0.63306457   -0.78034118   -0.42801448\n'
+                                                             'H      -0.38919244    0.98049560   -0.28294367\n'
+                                                             'H       0.00329661   -0.09013273    1.08846898\n'
+                                                             'H       1.01896040   -0.11002169   -0.37751083',
+                                          'label': 'CH4',
+                                          'long_thermo_description': "Bond corrections: {'C-H': 4}\n",
+                                          'mol': {'atom_order': rxn_dict_1['r_species'][0]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_1['r_species'][0]['mol']['atoms'],
+                                                  'multiplicity': 1,
+                                                  'props': {}},
+                                          'multiplicity': 1,
+                                          'number_of_rotors': 0},
+                                         {'bond_corrections': {'H-O': 1},
+                                          'cheap_conformer': 'O       0.00000000    0.00000000    0.61310000\n'
+                                                             'H       0.00000000    0.00000000   -0.61310000',
+                                          'label': 'OH',
+                                          'long_thermo_description': "Bond corrections: {'H-O': 1}\n",
+                                          'mol': {'atom_order': rxn_dict_1['r_species'][1]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_1['r_species'][1]['mol']['atoms'],
+                                                  'multiplicity': 2,
+                                                  'props': {}},
+                                          'multiplicity': 2,
+                                          'number_of_rotors': 0}],
+                           'reactants': ['CH4', 'OH'],
+                           }
+        self.assertEqual(rxn_dict_1, expected_dict_1)
+
+        rxn_dict_6 = self.rxn6.as_dict()
+        # The ``long_thermo_description`` attribute isn't deterministic (order could change)
+        expected_dict_6 = {'label': 'NH2 + N2H3 <=> NH3 + H2NN[S]',
+                           'family': 'Disproportionation',
+                           'multiplicity': 1,
+                           'p_species': [{'bond_corrections': {'H-N': 3},
+                                          'cheap_conformer': 'N       0.00064924   -0.00099698    0.29559292\n'
+                                                             'H      -0.41786606    0.84210396   -0.09477452\n'
+                                                             'H      -0.52039228   -0.78225292   -0.10002797\n'
+                                                             'H       0.93760911   -0.05885406   -0.10079043',
+                                          'label': 'NH3',
+                                          'long_thermo_description': "Bond corrections: {'H-N': 3}\n",
+                                          'mol': {'atom_order': rxn_dict_6['p_species'][0]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_6['p_species'][0]['mol']['atoms'],
+                                                  'multiplicity': 1,
+                                                  'props': {}},
+                                          'multiplicity': 1,
+                                          'number_of_rotors': 0},
+                                         {'adjlist': """multiplicity 1
+1 N u0 p0 c+1 {2,D} {3,S} {4,S}
+2 N u0 p2 c-1 {1,D}
+3 H u0 p0 c0 {1,S}
+4 H u0 p0 c0 {1,S}""",
+                                          'bond_corrections': {'H-N': 2, 'N=N': 1},
+                                          'cheap_conformer': 'N      -0.08201544    0.01567102    0.28740725\n'
+                                                             'N       1.12656450   -0.21525765   -0.48621674\n'
+                                                             'H      -0.50742562   -0.72901556    0.83982059\n'
+                                                             'H      -0.53712345    0.92860218    0.29862267',
+                                          'label': 'H2NN[S]',
+                                          'long_thermo_description': rxn_dict_6['p_species'][1]['long_thermo_description'],
+                                          'mol': {'atom_order': rxn_dict_6['p_species'][1]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_6['p_species'][1]['mol']['atoms'],
+                                                  'multiplicity': 1,
+                                                  'props': {}},
+                                          'multiplicity': 1,
+                                          'number_of_rotors': 0,
+                                          'original_label': 'H2NN(S)'}],
+                           'products': ['H2NN[S]', 'NH3'],
+                           'r_species': [{'bond_corrections': {'H-N': 2},
+                                          'cheap_conformer': 'N       0.00016375    0.40059499    0.00000000\n'
+                                                             'H      -0.83170922   -0.19995756    0.00000000\n'
+                                                             'H       0.83154548   -0.20063742    0.00000000',
+                                          'label': 'NH2',
+                                          'long_thermo_description': "Bond corrections: {'H-N': 2}\n",
+                                          'mol': {'atom_order': rxn_dict_6['r_species'][0]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_6['r_species'][0]['mol']['atoms'],
+                                                  'multiplicity': 2,
+                                                  'props': {}},
+                                          'multiplicity': 2,
+                                          'number_of_rotors': 0},
+                                         {'bond_corrections': {'H-N': 3, 'N-N': 1},
+                                          'cheap_conformer': 'N      -0.46751749    0.03795671    0.31180026\n'
+                                                             'N       0.79325823   -0.46038094   -0.24114357\n'
+                                                             'H      -1.19307188   -0.63034971    0.05027053\n'
+                                                             'H      -0.69753009    0.90231202   -0.17907452\n'
+                                                             'H       1.56486123    0.15046192    0.05814730',
+                                          'label': 'N2H3',
+                                          'long_thermo_description': rxn_dict_6['r_species'][1]['long_thermo_description'],
+                                          'mol': {'atom_order': rxn_dict_6['r_species'][1]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_6['r_species'][1]['mol']['atoms'],
+                                                  'multiplicity': 2,
+                                                  'props': {}},
+                                          'multiplicity': 2,
+                                          'number_of_rotors': 0}],
+                           'reactants': ['N2H3', 'NH2'],
+                           }
+        self.assertEqual(rxn_dict_6, expected_dict_6)
+
+    def test_from_dict(self):
+        """Test ARCReaction.from_dict()"""
+        rxn_dict = self.rxn1.as_dict()
+        rxn = ARCReaction(reaction_dict=rxn_dict)
+        self.assertEqual(rxn.label, 'CH4 + OH <=> CH3 + H2O')
+        self.assertEqual(rxn.multiplicity, 2)
+        self.assertEqual(rxn.charge, 0)
+        self.assertEqual(rxn.family, 'H_Abstraction')
+        self.assertEqual(rxn.family_own_reverse, True)
+        self.assertEqual(rxn.reactants, ['CH4', 'OH'])
+        self.assertEqual(rxn.products, ['CH3', 'H2O'])
+        self.assertIsNone(rxn.index)
+
+    def test_copy(self):
+        """Test the copy() method."""
+        rxn_copy = self.rxn1.copy()
+        self.assertIsNot(self.rxn1, rxn_copy)
+        self.assertEqual(rxn_copy.multiplicity, self.rxn1.multiplicity)
+        self.assertEqual(rxn_copy.label, self.rxn1.label)
+
+        rxn_copy = self.rxn8.copy()
+        self.assertIsNot(self.rxn8, rxn_copy)
+        self.assertEqual(self.rxn8.label, rxn_copy.label)
+        self.assertEqual(self.rxn8.multiplicity, rxn_copy.multiplicity)
+        self.assertEqual(self.rxn8.charge, rxn_copy.charge)
+        self.assertTrue(check_atom_map(self.rxn8))
+        self.assertTrue(check_atom_map(rxn_copy))
+        self.assertEqual(self.rxn8.atom_map, rxn_copy.atom_map)
+        self.assertEqual(tuple(spc.label for spc in self.rxn8.r_species),
+                         tuple(spc.label for spc in rxn_copy.r_species))
+        self.assertEqual(tuple(spc.label for spc in self.rxn8.p_species),
+                         tuple(spc.label for spc in rxn_copy.p_species))
+        self.assertNotIn(self.rxn8.r_species[0].mol.atoms[0].id, [atom.id for atom in rxn_copy.r_species[0].mol.atoms
+                                                                  + rxn_copy.p_species[0].mol.atoms])
+
+    def test_flip_reaction(self):
+        """Test the flip_reaction() method."""
+        flipped_rxn = self.rxn1.flip_reaction()
+        self.assertIsNot(self.rxn1, flipped_rxn)
+        self.assertEqual(flipped_rxn.multiplicity, self.rxn1.multiplicity)
+        self.assertNotEqual(flipped_rxn.label, self.rxn1.label)
+        for s1, s2 in zip(self.rxn1.r_species, flipped_rxn.p_species):
+            self.assertEqual(s1.label, s2.label)
+            self.assertTrue(s1.mol.is_isomorphic(s2.mol))
+        for s1, s2 in zip(self.rxn1.p_species, flipped_rxn.r_species):
+            self.assertEqual(s1.label, s2.label)
+            self.assertTrue(s1.mol.is_isomorphic(s2.mol))
+
+        flipped_rxn = self.rxn8.flip_reaction()
+        self.assertIsNot(self.rxn8, flipped_rxn)
+        self.assertNotEqual(self.rxn8.label, flipped_rxn.label)
+        self.assertEqual(self.rxn8.label.split('<=>')[0].strip(), flipped_rxn.label.split('<=>')[1].strip())
+        self.assertEqual(self.rxn8.label.split('<=>')[1].strip(), flipped_rxn.label.split('<=>')[0].strip())
+        self.assertEqual(self.rxn8.multiplicity, flipped_rxn.multiplicity)
+        self.assertEqual(self.rxn8.charge, flipped_rxn.charge)
+        self.assertTrue(check_atom_map(flipped_rxn))
+        self.assertEqual(self.rxn8.atom_map[0], 0)
+        self.assertEqual(self.rxn8.atom_map[5], 4)
+        self.assertEqual(flipped_rxn.atom_map[0], 0)
+        self.assertEqual(flipped_rxn.atom_map[4], 5)
+        self.assertEqual(tuple(spc.label for spc in self.rxn8.r_species),
+                         tuple(spc.label for spc in flipped_rxn.p_species))
+        self.assertEqual(tuple(spc.label for spc in self.rxn8.p_species),
+                         tuple(spc.label for spc in flipped_rxn.r_species))
+        self.assertNotIn(self.rxn8.r_species[0].mol.atoms[0].id, [atom.id for atom in flipped_rxn.r_species[0].mol.atoms
+                                                                  + flipped_rxn.p_species[0].mol.atoms])
+
+    def test_is_isomerization(self):
+        """Test the is_isomerization() method"""
+        self.assertFalse(self.rxn1.is_isomerization())
+        self.assertFalse(self.rxn2.is_isomerization())
+        self.assertTrue(self.rxn3.is_isomerization())
+        self.assertFalse(self.rxn4.is_isomerization())
+        self.assertFalse(self.rxn5.is_isomerization())
+        self.assertFalse(self.rxn6.is_isomerization())
+        self.assertFalse(self.rxn7.is_isomerization())
+        self.assertFalse(self.rxn8.is_isomerization())
+        self.assertFalse(self.rxn9.is_isomerization())
+
+    def test_rxn_family(self):
+        """Test that ARC gets the correct RMG family for different reactions"""
+        self.assertEqual(self.rxn1.family, 'H_Abstraction')
+        self.assertTrue(self.rxn1.family_own_reverse)
+        self.assertEqual(self.rxn2.family, 'Disproportionation')
+        self.assertFalse(self.rxn2.family_own_reverse)
+        self.assertEqual(self.rxn3.family, 'intra_H_migration')
+        self.assertTrue(self.rxn3.family_own_reverse)
+        self.assertEqual(self.rxn4.family, 'H_Abstraction')
+        self.rxn5.rmg_reaction_from_arc_species()
+        self.rxn5.check_attributes()
+        self.assertEqual(self.rxn5.family, 'H_Abstraction')
+        self.rxn9.rmg_reaction_from_arc_species()
+        self.rxn9.check_attributes()
+        self.assertEqual(self.rxn9.family, 'HO2_Elimination_from_PeroxyRadical')
+        rxn_9_flipped = self.rxn9.flip_reaction()
+        rxn_9_flipped.rmg_reaction_from_arc_species()
+        rxn_9_flipped.check_attributes()
+        self.assertEqual(rxn_9_flipped.family, 'HO2_Elimination_from_PeroxyRadical')
+        self.assertEqual(self.rxn10.family, 'H_Abstraction')
+        rxn_1 = ARCReaction(r_species=[ARCSpecies(label='C2H6', smiles='CC'),
+                                       ARCSpecies(label='CCOOj', smiles='CCO[O]')],
+                            p_species=[ARCSpecies(label='CCOOH', smiles='CCOO'),
+                                       ARCSpecies(label='C2H5', smiles='C[CH2]')])
+        rxn_1.check_attributes()
+        self.assertEqual(rxn_1.family, 'H_Abstraction')
+
+        # Test identifying the reaction family for with zwitterions read from Arkane YAML files
+        base_path = os.path.join(ARC_PATH, 'arc', 'testing', 'yml_testing', 'HNNO+NH3O=H2NO+NH2NO')
+        rxn2 = ARCReaction(r_species=[ARCSpecies(label='HNNO', smiles='[O-][N+]=N', yml_path=os.path.join(base_path, 'HNNO.yml')),
+                                      ARCSpecies(label='NH3O', smiles='[O-][NH3+]', yml_path=os.path.join(base_path, 'NH3O.yml'))],
+                           p_species=[ARCSpecies(label='H2NO', smiles='N[O]', yml_path=os.path.join(base_path, 'H2NO.yml')),
+                                      ARCSpecies(label='NH2NO', smiles='NN=O', yml_path=os.path.join(base_path, 'NH2NO.yml'))])
+        self.assertEqual(rxn2.family, 'H_Abstraction')
+
+    def test_charge_property(self):
+        """Test determining charge"""
+        self.assertEqual(self.rxn1.charge, 0)
+
+    def test_multiplicity_property(self):
+        """Test determining multiplicity"""
+        self.assertEqual(self.rxn1.multiplicity, 2)
+        self.assertEqual(self.rxn2.multiplicity, 1)
+        self.assertEqual(self.rxn3.multiplicity, 2)
+        self.assertEqual(self.rxn4.multiplicity, 3)
+        self.assertEqual(self.rxn5.multiplicity, 3)
+        self.assertEqual(self.rxn6.multiplicity, 1)
+        self.assertEqual(self.rxn7.multiplicity, 3)
+
+        # isomerization
+        rxn_1 = ARCReaction(reactants=['nC3H7'], products=['iC3H7'],
+                            r_species=[ARCSpecies(label='nC3H7', smiles='[CH2]CC')],
+                            p_species=[ARCSpecies(label='iC3H7', smiles='C[CH]C')])
+        self.assertEqual(rxn_1.multiplicity, 2)
+        rxn_2 = ARCReaction(reactants=['CC=O'], products=['C=COH'],
+                            r_species=[ARCSpecies(label='CC=O', smiles='CC=O')],
+                            p_species=[ARCSpecies(label='C=COH', smiles='C=CO')])
+        self.assertEqual(rxn_2.multiplicity, 1)
+
+        # unimolecular
+        rxn_3 = ARCReaction(reactants=['H', 'OH'], products=['H2O'],
+                            r_species=[ARCSpecies(label='H', smiles='[H]'), ARCSpecies(label='OH', smiles='[OH]')],
+                            p_species=[ARCSpecies(label='H2O', smiles='O')])
+        self.assertEqual(rxn_3.multiplicity, 1)
+
+        # Reactions for which the multiplicity was wrongly determined before code fixes:
+        rxn_4 = ARCReaction(reactants=['H', 'HO2'], products=['OH', 'OH'],
+                            r_species=[ARCSpecies(label='H', smiles='[H]'), ARCSpecies(label='HO2', smiles='O[O]')],
+                            p_species=[ARCSpecies(label='OH', smiles='[OH]'), ARCSpecies(label='OH', smiles='[OH]')])
+        self.assertEqual(rxn_4.multiplicity, 1)
+
+        rxn_5 = ARCReaction(r_species=[ARCSpecies(label='N', smiles='[N]'), ARCSpecies(label='HNO', smiles='N=O')],
+                            p_species=[ARCSpecies(label='NO', smiles='[N]=O'),
+                                       ARCSpecies(label='NH', smiles='[NH]')])
+        self.assertEqual(rxn_5.multiplicity, 4)
+        rxn_5 = ARCReaction(r_species=[ARCSpecies(label='N', smiles='[N]'), ARCSpecies(label='HNO', smiles='N=O')],
+                            p_species=[ARCSpecies(label='NO', smiles='[N]=O'), ARCSpecies(label='NH', smiles='[NH]')])
+        self.assertEqual(rxn_5.multiplicity, 4)
+
+    def test_check_atom_balance(self):
+        """Test the Reaction check_atom_balance method"""
+
+        # A normal reaction
+        rxn1 = ARCReaction(reactants=['CH4', 'OH'], products=['CH3', 'H2O'],
+                           r_species=[ARCSpecies(label='CH4', smiles='C'),
+                                      ARCSpecies(label='OH', smiles='[OH]')],
+                           p_species=[ARCSpecies(label='CH3', smiles='[CH3]'),
+                                      ARCSpecies(label='H2O', smiles='O')])
+        self.assertTrue(rxn1.check_atom_balance())
+
+        # A reaction with the same species twice on one side
+        rxn3 = ARCReaction(reactants=['CH4', 'OH', 'H2O'], products=['CH3', 'H2O', 'H2O'],
+                           r_species=[ARCSpecies(label='CH4', smiles='C'),
+                                      ARCSpecies(label='OH', smiles='[OH]'),
+                                      ARCSpecies(label='H2O', smiles='O')],
+                           p_species=[ARCSpecies(label='CH3', smiles='[CH3]'),
+                                      ARCSpecies(label='H2O', smiles='O')])
+        self.assertTrue(rxn3.check_atom_balance())
+
+        # Another reaction with the same species twice on one side
+        rxn4 = ARCReaction(reactants=['OH', 'OH'], products=['O', 'H2O'],
+                           r_species=[ARCSpecies(label='OH', smiles='[OH]')],
+                           p_species=[ARCSpecies(label='O', smiles='[O]'),
+                                      ARCSpecies(label='H2O', smiles='O')])
+        self.assertTrue(rxn4.check_atom_balance())
+
+        # Another reaction with the same species twice on one side, reading from the reaction label
+        nh2 = ARCSpecies(label='NH2', smiles='[NH2]')
+        h = ARCSpecies(label='H', smiles='[H]')
+        n2h3 = ARCSpecies(label='N2H3', smiles='[NH]N')
+        rxn_label = 'NH2 + NH2 <=> H + N2H3'
+        rxn5 = ARCReaction(reaction_dict={'label': rxn_label}, species_list=[nh2, h, n2h3])
+        self.assertTrue(rxn5.check_atom_balance())
+        rxn5_flipped = rxn5.flip_reaction()
+        self.assertTrue(rxn5_flipped.check_atom_balance())
+
+        # Legitimate reactions that previously failed in the atom balance test
+        rxn6 = ARCReaction(reactants=['NH', '[O-][N+](=N)N'], products=['NH2', '[N-]=[N+]([O])N'],
+                           r_species=[ARCSpecies(label='NH', smiles='[NH]'),
+                                      ARCSpecies(label='[O-][N+](=N)N', smiles='[O-][N+](=N)N')],
+                           p_species=[ARCSpecies(label='NH2', smiles='[NH2]'),
+                                      ARCSpecies(label='[N-]=[N+]([O])N', smiles='[N-]=[N+]([O])N')])
+        self.assertTrue(rxn6.check_atom_balance())
+
+        rxn7 = ARCReaction(reactants=['N3O2', 'HON'], products=['NO', 'HN3O2'],
+                           r_species=[ARCSpecies(label='N3O2', smiles='[N-]=[N+](N=O)[O]'),
+                                      ARCSpecies(label='HON', smiles='[OH+]=[N-]')],
+                           p_species=[ARCSpecies(label='NO', smiles='[N]=O'),
+                                      ARCSpecies(label='HN3O2', smiles='[O-][N+](=N)N=O')])
+        self.assertTrue(rxn7.check_atom_balance())
+
+        # A reaction that involves charged species
+        rxn8 = ARCReaction(reactants=['C6CNC3', 'OH'], products=['C6COH', 'NC3'],
+                           r_species=[ARCSpecies(label='C6CNC3', smiles='c1ccccc1C[N+](C)(C)C', charge=1, multiplicity=1),
+                                      ARCSpecies(label='OH', smiles='[OH-]', charge=-1, multiplicity=1)],
+                           p_species=[ARCSpecies(label='C6COH', smiles='c1ccccc1CO'),
+                                      ARCSpecies(label='NC3', smiles='CN(C)C')])
+        self.assertTrue(rxn8.check_atom_balance())
+
+        # A *non*-balanced reaction
+        with self.assertRaises(ReactionError):
+            ARCReaction(reactants=['CH4', 'OH'], products=['CH4', 'H2O'],
+                        r_species=[ARCSpecies(label='CH4', smiles='C'),
+                                   ARCSpecies(label='OH', smiles='[OH]')],
+                        p_species=[ARCSpecies(label='CH4', smiles='C'),
+                                   ARCSpecies(label='H2O', smiles='O')])
+
+    def test_get_species_count(self):
+        """Test the get_species_count() method"""
+        rxn1 = ARCReaction(reactants=['CH4', 'OH', 'H2O'], products=['CH3', 'H2O', 'H2O'])
+        spc1 = ARCSpecies(label='OH', smiles='[OH]')
+        spc2 = ARCSpecies(label='H2O', smiles='O')
+        # check by species
+        self.assertEqual(rxn1.get_species_count(species=spc1, well=0), 1)
+        self.assertEqual(rxn1.get_species_count(species=spc1, well=1), 0)
+        self.assertEqual(rxn1.get_species_count(species=spc2, well=0), 1)
+        self.assertEqual(rxn1.get_species_count(species=spc2, well=1), 2)
+        # check by label
+        self.assertEqual(rxn1.get_species_count(label=spc1.label, well=0), 1)
+        self.assertEqual(rxn1.get_species_count(label=spc1.label, well=1), 0)
+        self.assertEqual(rxn1.get_species_count(label=spc2.label, well=0), 1)
+        self.assertEqual(rxn1.get_species_count(label=spc2.label, well=1), 2)
+
+        h2nn = ARCSpecies(label='H2NN(T)', smiles='[N]N')
+        n2h2 = ARCSpecies(label='N2H4', smiles='NN')
+        n2h3 = ARCSpecies(label='N2H3', smiles='[NH]N')
+        rxn2 = ARCReaction(r_species=[h2nn, n2h2], p_species=[n2h3, n2h3])
+        self.assertEqual(rxn2.get_species_count(label=n2h3.label, well=1), 2)
+
+    def test_get_reactants_and_products(self):
+        """Test getting reactants and products"""
+        self.rxn1.remove_dup_species()
+        reactants, products = self.rxn1.get_reactants_and_products(arc=True)
+        for spc in reactants + products:
+            self.assertIsInstance(spc, ARCSpecies)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+
+        reactants, products = self.rxn1.get_reactants_and_products(arc=False)
+        for spc in reactants + products:
+            self.assertIsInstance(spc, Species)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+
+        reactants, products = self.rxn5.get_reactants_and_products(arc=True)
+        for spc in reactants + products:
+            self.assertIsInstance(spc, ARCSpecies)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+        self.assertEqual(reactants[0].label, reactants[1].label)
+
+        reactants, products = self.rxn5.get_reactants_and_products(arc=False)
+        for spc in reactants + products:
+            self.assertIsInstance(spc, Species)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+        self.assertNotEqual(products[0].label, products[1].label)
+
+        h2nn = ARCSpecies(label='H2NN(T)', smiles='[N]N')
+        n2h2 = ARCSpecies(label='N2H4', smiles='NN')
+        n2h3 = ARCSpecies(label='N2H3', smiles='[NH]N')
+        rxn1 = ARCReaction(r_species=[h2nn, n2h2], p_species=[n2h3, n2h3])
+        reactants, products = rxn1.get_reactants_and_products(arc=True, return_copies=False)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+        self.assertIs(products[0], products[1])
+        reactants, products = rxn1.get_reactants_and_products(arc=True, return_copies=True)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+        self.assertIsNot(products[0], products[1])
+
+    def test_get_expected_changing_bonds(self):
+        """Test the get_expected_changing_bonds() method."""
+        expected_breaking_bonds, expected_forming_bonds = self.rxn11.get_expected_changing_bonds(
+            r_label_dict={'*1': 1, '*2': 2, '*3': 6})
+        self.assertEqual(expected_breaking_bonds, [(2, 6)])
+        self.assertEqual(expected_forming_bonds, [(1, 6)])
+
+    def test_get_number_of_atoms_in_reaction_zone(self):
+        """Test the get_number_of_atoms_in_reaction_zone() method."""
+        self.assertEqual(self.rxn1.get_number_of_atoms_in_reaction_zone(), 3)  # H_Abstraction
+        self.assertEqual(self.rxn2.get_number_of_atoms_in_reaction_zone(), 4)  # Disprop
+        self.assertEqual(self.rxn3.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn4.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn5.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn6.get_number_of_atoms_in_reaction_zone(), 4)  # Disprop
+        self.assertEqual(self.rxn7.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn8.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn9.get_number_of_atoms_in_reaction_zone(), 5)  # HO2_Elimination_from_PeroxyRadical
+        self.assertEqual(self.rxn10.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn11.get_number_of_atoms_in_reaction_zone(), 3)
+
+    def test_get_atom_map(self):
+        """Test getting an atom map for a reaction"""
+
+        # 1. trivial unimolecular: H2O <=> H2O
+        h2o_xyz_1 = {'symbols': ('O', 'H', 'H'), 'isotopes': (16, 1, 1),
+                     'coords': ((-0.0003283189391273643, 0.39781490416473486, 0.0),
+                                (-0.7633034507689803, -0.19953755103743254, 0.0),
+                                (0.7636317697081081, -0.19827735312730177, 0.0))}
+        r_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_1)
+        p_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_1)
+        rxn_1 = ARCReaction(reactants=['H2O'], products=['H2O'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn_1.atom_map, [0, 1, 2])
+        self.assertTrue(check_atom_map(rxn_1))
+
+        # 2. trivial unimolecular with an intentional mixed atom order: H2O <=> H2O
+        h2o_xyz_2 = {'symbols': ('H', 'H', 'O'), 'isotopes': (1, 1, 16),
+                     'coords': ((-0.7633034507689803, -0.19953755103743254, 0.0),
+                                (0.7636317697081081, -0.19827735312730177, 0.0),
+                                (-0.0003283189391273643, 0.39781490416473486, 0.0))}
+        p_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_2)
+        rxn_2 = ARCReaction(reactants=['H2O'], products=['H2O'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn_2.atom_map, [2, 0, 1])
+        self.assertTrue(check_atom_map(rxn_2))
+
+        # 3. trivial bimolecular: H + CH3NH2 <=> H2 + CH2NH2
+        ch3nh2_xyz = {'coords': ((-0.5734111454228507, 0.0203516083213337, 0.03088703933770556),
+                                 (0.8105595891860601, 0.00017446498908627427, -0.4077728757313545),
+                                 (-1.1234549667791063, -0.8123899006368857, -0.41607711106038836),
+                                 (-0.6332220120842996, -0.06381791823047896, 1.1196983583774054),
+                                 (-1.053200912106195, 0.9539501896695028, -0.27567270246542575),
+                                 (1.3186422395164141, 0.7623906284020254, 0.038976118645639976),
+                                 (1.2540872076899663, -0.8606590725145833, -0.09003882710357966)),
+                      'isotopes': (12, 14, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'N', 'H', 'H', 'H', 'H', 'H')}
+        ch2nh2_xyz = {'coords': ((0.6919493009211066, 0.054389375309083846, 0.02065422596281878),
+                                 (1.3094508022837807, -0.830934909576592, 0.14456347719459348),
+                                 (1.1649142139806816, 1.030396183273415, 0.08526955368597328),
+                                 (-0.7278194451655412, -0.06628299353512612, -0.30657582460750543),
+                                 (-1.2832757211903472, 0.7307667658607352, 0.00177732009031573),
+                                 (-1.155219150829674, -0.9183344213315149, 0.05431124767380799)),
+                      'isotopes': (12, 1, 1, 14, 1, 1),
+                      'symbols': ('C', 'H', 'H', 'N', 'H', 'H')}
+        r_1 = ARCSpecies(label='H', smiles='[H]', xyz={'coords': ((0, 0, 0),), 'isotopes': (1,), 'symbols': ('H',)})
+        r_2 = ARCSpecies(label='CH3NH2', smiles='CN', xyz=ch3nh2_xyz)
+        p_1 = ARCSpecies(label='H2', smiles='[H][H]', xyz=self.h2_xyz)
+        p_2 = ARCSpecies(label='CH2NH2', smiles='[CH2]N', xyz=ch2nh2_xyz)
+        rxn_3 = ARCReaction(reactants=['H', 'CH3NH2'], products=['H2', 'CH2NH2'],
+                            r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn_3.family, "H_Abstraction")
+        self.assertIn(rxn_3.atom_map[0], [0, 1])
+        self.assertEqual(rxn_3.atom_map[1:3], [2, 5])
+        for index in [3, 4, 5]:
+            self.assertIn(rxn_3.atom_map[index], [0, 1, 3, 4])
+        self.assertIn(rxn_3.atom_map[6:], [[7, 6], [6, 7]])
+        self.assertTrue(check_atom_map(rxn_3))
+
+        # 4. trivial bimolecular in reverse order: H + CH3NH2 <=> CH2NH2 + H2
+        rxn_4 = ARCReaction(reactants=['H', 'CH3NH2'], products=['CH2NH2', 'H2'],
+                            r_species=[r_1, r_2], p_species=[p_2, p_1])
+        self.assertIn(rxn_4.atom_map[0], [6, 7])
+        self.assertEqual(rxn_4.atom_map[1:3], [0, 3])
+        for index in [3, 4, 5]:
+            self.assertIn(rxn_4.atom_map[index], [1, 2, 6, 7])
+        self.assertIn(rxn_4.atom_map[6:], [[5, 4], [4, 5]])
+        self.assertTrue(check_atom_map(rxn_4))
+
+        # H_Abstraction: C3H6O + C4H9O <=> C3H5O + C4H10O
+        c3h6o_xyz = {'coords': ((-1.0614352911982476, -0.35086070951203013, 0.3314546936475969),
+                                (0.08232694092180896, 0.5949821397504677, 0.020767511136565348),
+                                (1.319643623472743, -0.1238222051358961, -0.4579284002686819),
+                                (1.4145501246584122, -1.339374145335546, -0.5896335370976351),
+                                (-0.7813545474862899, -1.0625754884160945, 1.1151404910689675),
+                                (-1.3481804813952152, -0.9258389945508673, -0.5552942813558058),
+                                (-1.9370566523150816, 0.2087367432207233, 0.6743848589525232),
+                                (-0.2162279757671984, 1.3021306884228383, -0.7596873819624604),
+                                (0.35220978385921775, 1.1650050778348893, 0.9154971248602527),
+                                (2.1755244752498673, 0.5316168937214946, -0.6947010789813145)),
+                     'isotopes': (12, 12, 12, 16, 1, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'C', 'O', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c4h9o_xyz = {'coords': ((0.025711531222639566, 1.5002469234994276, -0.018809721320361607),
+                                (-0.2501237905589279, 2.283276320160058, 0.6795778782867752),
+                                (0.21710649528235348, 1.7701501165266882, -1.0518607878262018),
+                                (-0.1296127183749531, 0.05931626777072968, 0.3829802045651552),
+                                (-1.5215969202773243, -0.4341372833972907, -0.0024458040153687616),
+                                (0.954275466146204, -0.8261822387409435, -0.2512878552942834),
+                                (2.238645869558612, -0.5229077195628998, 0.2868843893740711),
+                                (-0.022719509344805086, 0.012299638536749403, 1.47391586262432),
+                                (-1.6734988982808552, -1.4656213151526711, 0.3333615031669381),
+                                (-1.6708084550075688, -0.40804497485420527, -1.0879383468423085),
+                                (-2.3005261427143897, 0.18308085969254126, 0.45923715033920876),
+                                (0.7583076310662862, -1.882720433150506, -0.04089782108496264),
+                                (0.9972006722528377, -0.7025586995487184, -1.3391950754631268),
+                                (2.377638769033351, 0.43380253822255727, 0.17647842348371048)),
+                     'isotopes': (12, 1, 1, 12, 12, 12, 16, 1, 1, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'H', 'H', 'C', 'C', 'C', 'O', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c3h5o_xyz = {'coords': ((-1.1339526749599567, -0.11366348271898848, -0.17361178233231772),
+                                (0.1315989608873882, 0.19315012600914244, 0.5375291058021542),
+                                (0.12186476447223683, 0.5479023323381329, 1.5587521800625246),
+                                (1.435623589506148, 0.026762256080503182, -0.11697684942586563),
+                                (1.5559845484585495, -0.3678359306766861, -1.2677014903374604),
+                                (-1.6836994309836657, -0.8907558916446712, 0.3657463577153353),
+                                (-1.7622426221647125, 0.7810307051429465, -0.21575166529131876),
+                                (-0.9704526962734873, -0.4619573344933834, -1.1970278328709658),
+                                (2.3052755610575106, 0.2853672199629854, 0.5090419766779545)),
+                     'isotopes': (12, 12, 1, 12, 16, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'H', 'C', 'O', 'H', 'H', 'H', 'H')}
+        c4h10o_xyz = {'coords': ((-1.0599869990613344, -1.2397714287161459, 0.010871360821665921),
+                                 (-0.15570197396874313, -0.0399426912154684, -0.2627503141760959),
+                                 (-0.8357120092418682, 1.2531917172190083, 0.1920887922885465),
+                                 (1.2013757682054618, -0.22681093996845836, 0.42106399857821075),
+                                 (2.0757871909243337, 0.8339710961541049, 0.05934908325727899),
+                                 (-1.2566363886319676, -1.3536924078596617, 1.082401336123387),
+                                 (-0.5978887839926055, -2.1649950925769703, -0.3492714363488459),
+                                 (-2.0220571570609596, -1.1266512469159389, -0.4999630281827645),
+                                 (0.0068492778433242255, 0.03845056912064928, -1.3453078463310726),
+                                 (-0.22527545723287978, 2.1284779433126504, -0.05264318253022085),
+                                 (-1.804297837475001, 1.3767516368254167, -0.30411519687565475),
+                                 (-1.0079707678533625, 1.2514371624519658, 1.2738106811073706),
+                                 (1.0967232048111195, -0.23572903005857432, 1.511374071529777),
+                                 (1.6637048773271081, -1.1686406202494035, 0.10718319440789557),
+                                 (2.9210870554073614, 0.6739533324768243, 0.512528859867013)),
+                      'isotopes': (12, 12, 12, 12, 16, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'O', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O', xyz=c3h6o_xyz)
+        r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO', xyz=c4h9o_xyz)
+        p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=c3h5o_xyz)
+        p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=c4h10o_xyz)
+        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        atom_map = rxn.atom_map
+        self.assertEqual(atom_map[0:4], [0, 1, 3, 4])
+        self.assertIn(atom_map[4], [5,6, 7])
+        self.assertIn(atom_map[5], [5,6, 7])
+        self.assertIn(atom_map[6], [5,6, 7])
+        self.assertIn(atom_map[7], [2, 14, 15, 16, 18, 19, 20])
+        self.assertIn(atom_map[8], [2, 14, 15, 16, 18, 19, 20])
+        self.assertTrue(any(entry == 2 for entry in [atom_map[7], atom_map[8]]))
+        self.assertEqual(atom_map[9], 8)
+        self.assertIn(atom_map[10], [9,11])
+        self.assertIn(atom_map[11], [14, 15, 16,18,19,20])
+        self.assertIn(atom_map[12], [14, 15, 16,18,19,20])
+        self.assertEqual(atom_map[13],10)
+        self.assertIn(atom_map[14], [9,11])
+        self.assertEqual(atom_map[15:17], [12,13])
+        self.assertEqual(atom_map[17],17)
+        self.assertIn(atom_map[18], [14, 15, 16,18,19,20])
+        self.assertIn(atom_map[19], [14, 15, 16,18,19,20])
+        self.assertIn(atom_map[20], [14, 15, 16,18,19,20])
+        self.assertIn(atom_map[21], [21,22])
+        self.assertIn(atom_map[22], [21,22])
+        self.assertEqual(atom_map[23],23)
+        self.assertTrue(check_atom_map(rxn))
+
+        # H_Abstraction: NH + N2H3 <=> NH2 + N2H2(T)
+        n2h3_xyz = {'coords': ((-0.470579649119187, 0.04999660847282449, 0.3054306465848634),
+                               (0.7822241718336367, -0.48270144244781193, -0.23341826421899858),
+                               (1.5677258653370059, 0.10203349472372605, 0.08145841384293159),
+                               (-0.6670140616222734, 0.9245291856920813, -0.1819911659528955),
+                               (-1.212356326429186, -0.5938578464408176, 0.028520369744099196)),
+                    'isotopes': (14, 14, 1, 1, 1),
+                    'symbols': ('N', 'N', 'H', 'H', 'H')}
+        nh2_xyz = {'coords': ((0.0001637451536497341, 0.4005949879135532, 0.0),
+                              (-0.8317092208339203, -0.19995756341639623, 0.0),
+                              (0.8315454756802706, -0.20063742449715688, 0.0)),
+                   'isotopes': (14, 1, 1),
+                   'symbols': ('N', 'H', 'H')}
+        n2h2_t_xyz = {'coords': ((0.5974274138372041, -0.41113104979405946, 0.08609839663782763),
+                                 (1.421955422639823, 0.19737093442024492, 0.02508578507394823),
+                                 (-0.5974274348582206, 0.41113108883884353, -0.08609846602622732),
+                                 (-1.4219554016188147, -0.19737097346502322, -0.02508571568554942)),
+                      'isotopes': (14, 1, 14, 1),
+                      'symbols': ('N', 'H', 'N', 'H')}
+        r_1 = ARCSpecies(label='NH', smiles='[NH]', xyz=self.nh_xyz)
+        r_2 = ARCSpecies(label='N2H3', smiles='N[NH]', xyz=n2h3_xyz)
+        p_1 = ARCSpecies(label='NH2', smiles='[NH2]', xyz=nh2_xyz)
+        p_2 = ARCSpecies(label='N2H2(T)', smiles='[NH][NH]', xyz=n2h2_t_xyz)
+        rxn = ARCReaction(reactants=['NH', 'N2H3'], products=['NH2', 'N2H2(T)'],
+                          r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[0], 0)
+        self.assertIn(rxn.atom_map[1], [1, 2])
+        self.assertIn(rxn.atom_map[2], [3, 5])
+        self.assertIn(rxn.atom_map[3], [3, 5])
+        self.assertIn(rxn.atom_map[4], [4, 6])
+        self.assertIn(rxn.atom_map[5], [1, 2, 4, 6])
+        self.assertIn(rxn.atom_map[6], [1, 2, 4, 6])
+        self.assertTrue(any(rxn.atom_map[index] in [1, 2] for index in [5, 6]))
+        self.assertTrue(check_atom_map(rxn))
+
+        # Cyclopentadiene_scission: C6H6 <=> C6H6_2
+        c6h6_a_xyz = {'coords': ((1.465264096022479, 0.3555098886638667, 0.15268159347190322),
+                                 (0.4583546746026421, 1.1352991023740606, -0.26555553330413073),
+                                 (-0.7550043760214846, 0.35970165318809594, -0.5698935045151712),
+                                 (-1.485327813119871, -0.35660657095915016, 0.46119177830578917),
+                                 (-0.3414477960946828, -1.060779229397218, -0.11686056681841692),
+                                 (0.9879417277856641, -1.006839916409751, 0.12489717473407935),
+                                 (2.4630837864551887, 0.6629994259328668, 0.4197578798464181),
+                                 (0.5110882588097015, 2.2100951208919897, -0.3734820378556644),
+                                 (-1.1192886361027838, 0.384286081689225, -1.5897813181530946),
+                                 (-2.453224961870327, -0.7758708758357847, 0.2158838729688473),
+                                 (-1.3859013659398718, -0.054382091828296085, 1.4971154213962072),
+                                 (1.6544624054733257, -1.8534125883098933, 0.0440452399232336)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c6h6_b_xyz = {'coords': ((-1.474267041853848, 0.27665693719971857, -0.31815898666696507),
+                                 (-0.25527025747758825, 1.1936776717612125, -0.2432148642540069),
+                                 (0.9917471212521393, 0.7578589393970138, 0.059037260524552534),
+                                 (1.2911962562420976, -0.6524103892231805, 0.34598643264742923),
+                                 (0.321535921890914, -1.5867102018006056, 0.32000545365633654),
+                                 (-0.9417407846918554, -1.043897260224426, -0.002820356559266387),
+                                 (-2.2262364004658077, 0.5956762298613206, 0.40890113659975075),
+                                 (-1.90597332290244, 0.31143075666839354, -1.3222845692785703),
+                                 (-0.4221153027089989, 2.2469871640348815, -0.4470234892644997),
+                                 (1.824518548011024, 1.4543788790156666, 0.0987362566117616),
+                                 (2.3174577767359237, -0.9162726684959432, 0.5791638390925197),
+                                 (0.4791474859684761, -2.637376058194065, 0.5216718868909702)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C6H6_1', smiles='C1=CC2CC2=C1', xyz=c6h6_a_xyz)
+        p_1 = ARCSpecies(label='C6H6_b', xyz=c6h6_b_xyz, adjlist="""multiplicity 1
+                                                                    1  C u0 p0 c0 {2,S} {6,S} {7,S} {8,S}
+                                                                    2  C u0 p0 c0 {1,S} {3,D} {9,S}
+                                                                    3  C u0 p0 c0 {2,D} {4,S} {10,S}
+                                                                    4  C u0 p0 c0 {3,S} {5,D} {11,S}
+                                                                    5  C u0 p0 c0 {4,D} {6,S} {12,S}
+                                                                    6  C u0 p1 c0 {1,S} {5,S}
+                                                                    7  H u0 p0 c0 {1,S}
+                                                                    8  H u0 p0 c0 {1,S}
+                                                                    9  H u0 p0 c0 {2,S}
+                                                                    10 H u0 p0 c0 {3,S}
+                                                                    11 H u0 p0 c0 {4,S}
+                                                                    12 H u0 p0 c0 {5,S}""")
+        rxn = ARCReaction(reactants=['C6H6_1'], products=['C6H6_b'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [1, 4, 2, 0, 5, 3, 10, 9, 8, 7, 6, 11])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Disproportionation: HO2 + NHOH <=> NH2OH + O2
+        nhoh_xyz = {'coords': ((0.5055094877826753, 0.03248552573561613, -0.443416250587286),
+                               (1.392367115364475, -0.021750569314658803, 0.07321920788090872),
+                               (-0.570163178752975, -0.035696714715839996, 0.48914535186936214),
+                               (-1.3277134243941644, 0.024961758294888944, -0.11894830916297996)),
+                    'isotopes': (14, 1, 16, 1), 'symbols': ('N', 'H', 'O', 'H')}
+        nh2oh_xyz = {'coords': ((-0.442357984214193, 0.12755746178283767, -0.283450834226086),
+                                (0.8066044298181865, -0.19499391813986608, 0.38695057103192726),
+                                (-0.9953709942529645, -0.7170738803381369, -0.11579136415085267),
+                                (-0.8349557675364339, 0.8418549600381088, 0.33540420712720587),
+                                (1.4660803161854115, -0.05734462334294334, -0.32311257978218827)),
+                     'isotopes': (14, 16, 1, 1, 1), 'symbols': ('N', 'O', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='NHOH', smiles='[NH]O', xyz=nhoh_xyz)
+        r_2 = ARCSpecies(label='HO2', smiles='O[O]', xyz=self.ho2_xyz)
+        p_1 = ARCSpecies(label='O2', smiles='[O][O]', xyz=self.o2_xyz)
+        p_2 = ARCSpecies(label='NH2OH', smiles='NO', xyz=nh2oh_xyz)
+        rxn = ARCReaction(reactants=['NHOH', 'HO2'], products=['O2', 'NH2OH'],
+                          r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[0], 2)
+        for index in [1, 6]:
+            self.assertIn(rxn.atom_map[index], [4, 5])
+        self.assertEqual(rxn.atom_map[2], 3)
+        self.assertEqual(rxn.atom_map[3], 6)
+        for index in [4, 5]:
+            self.assertIn(rxn.atom_map[index], [0, 1])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Intra_Disproportionation: C10H10_a <=> C10H10_b
+        c10h10_a_xyz = {'coords': ((3.1623638230700997, 0.39331289450005563, -0.031839117414963584),
+                                   (1.8784852381397288, 0.037685951926618944, -0.13659028131444134),
+                                   (0.9737380560194014, 0.5278617594060281, -1.1526858375270472),
+                                   (1.2607098516126556, 1.1809007875206383, -1.9621017164412065),
+                                   (-0.36396095305912823, -0.13214785064139675, -1.0200667625809143),
+                                   (-1.5172464644867296, 0.8364138939810618, -1.0669384323486588),
+                                   (-2.4922101649968655, 0.8316551483126366, -0.14124720277902958),
+                                   (-2.462598061982958, -0.09755474191953761, 0.9703503187569243),
+                                   (-1.4080417204047313, -0.8976377310686736, 1.1927020968566089),
+                                   (-0.27981087345916755, -0.8670643393461046, 0.29587765657632165),
+                                   (1.1395623815572733, -0.9147118621123697, 0.771368745020215),
+                                   (3.7901243915692864, -0.006544237180536178, 0.7580206603561134),
+                                   (3.6186251824572455, 1.0920401631166292, -0.725695658374561),
+                                   (-0.4799044636709365, -0.8577283498506146, -1.8345168113636874),
+                                   (-1.5704890060131314, 1.527002009812866, -1.902575985299536),
+                                   (-3.3260277144990296, 1.5238536460491903, -0.20338465526703625),
+                                   (-3.311126364299293, -0.09969554359088921, 1.6478137927333953),
+                                   (-1.3707042898204835, -1.549541647625315, 2.0589774409040964),
+                                   (1.5338362221707007, -1.9310023570889727, 0.6663504223502944),
+                                   (1.2246749300961473, -0.5970975942012858, 1.816181327157103)),
+                        'isotopes': (12, 12, 12, 1, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                        'symbols': ('C', 'C', 'C', 'H', 'C', 'C', 'C', 'C', 'C', 'C', 'C',
+                                    'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c10h10_b_xyz = {'coords': ((3.247237794328524, -0.13719671162966918, 0.19555833918937052),
+                                   (1.9094861712282774, -0.08067655688828143, 0.14898941432495702),
+                                   (0.9973729357914858, -1.2703386896415134, -0.09322848415119056),
+                                   (-0.37904449715218924, -0.6747166782032148, -0.049044448345326556),
+                                   (-0.32906812544096026, 0.704634441388649, 0.189424753183012),
+                                   (-1.4900181263846768, 1.4572613706024167, 0.2695747550348709),
+                                   (-2.715200996994148, 0.8069241052920498, 0.10660938013945513),
+                                   (-2.765284083663716, -0.5753713833636181, -0.13236922431004927),
+                                   (-1.5909002849280705, -1.3270914347507115, -0.21179882275795825),
+                                   (1.0862366144301145, 1.1823049698313937, 0.33079658088902575),
+                                   (3.8424769924852367, 0.7530758608805569, 0.37314678191170336),
+                                   (3.7762437608797406, -1.0749685445597326, 0.05710603017340202),
+                                   (1.1128196175313243, -2.0170485762246773, 0.6986324476157837),
+                                   (1.187449599052061, -1.7129398667445945, -1.0760419644685346),
+                                   (-1.453108430051206, 2.525963604437891, 0.45426129138400156),
+                                   (-3.639988653002051, 1.3756767310587803, 0.16518163487425436),
+                                   (-3.7283956370857467, -1.0643593255501977, -0.2566648708585298),
+                                   (-1.631427244782937, -2.3956407728893367, -0.3966116183664473),
+                                   (1.3188711462571718, 1.9143096670969255, -0.4489453399950017),
+                                   (1.2442414475018486, 1.6101977898569013, 1.3257284397785851)),
+                        'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                        'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C',
+                                    'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C10H10_a', smiles='C=C1[CH]C2C=CC=C[C]2C1', xyz=c10h10_a_xyz, multiplicity=3)
+        p_1 = ARCSpecies(label='C10H10_b', smiles='C=C1CC2=C(C=CC=C2)C1', xyz=c10h10_b_xyz)
+        rxn = ARCReaction(reactants=['C10H10_a'], products=['C10H10_b'],
+                          r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [0, 1, 8, 13, 3, 2, 7, 6, 5, 4, 9, 10, 17, 12, 11, 16, 15, 14, 19, 18])
+        self.assertTrue(check_atom_map(rxn))
+
+        # intra_NO2_ONO_conversion: C2H5NO2 <=> C2H5ONO
+        c6h5_xyz = {'coords': ((1.8953828083622057, 0.8695975650550358, 0.6461465212661076),
+                               (1.3601473931706598, -0.04212583715410005, 0.0034200061443233247),
+                               (1.8529583069008781, -0.6310931351538215, -0.9666668585141432),
+                               (-0.010154355673379136, -0.4652844276756663, 0.43320585211058743),
+                               (-1.0281604639422022, 0.36855062612122236, -0.3158851121891869),
+                               (-0.11071296591935365, -1.5314728469286516, 0.20909234121344752),
+                               (-0.07635985361458197, -0.31625218083177237, 1.5151037167736001),
+                               (-2.042322710601489, 0.08102183703582924, -0.021667016484293297),
+                               (-0.9033569412063314, 1.436005790671757, -0.10388682333330314),
+                               (-0.937421217476434, 0.23105260886017234, -1.3988626269871478)),
+                    'isotopes': (16, 14, 16, 12, 12, 1, 1, 1, 1, 1),
+                    'symbols': ('O', 'N', 'O', 'C', 'C', 'H', 'H', 'H', 'H', 'H')}
+        c7h5o_xyz = {'coords': ((-1.3334725178745668, 0.2849178019354427, 0.4149005134933577),
+                                (-0.08765353373275289, 0.24941420749682627, -0.4497882845360618),
+                                (1.0488580188184402, 0.3986394744609146, 0.39515448276833964),
+                                (2.2292240798482883, 0.36629637181188207, -0.4124684043339001),
+                                (3.2413605054484185, 0.4928521621538312, 0.283008378837631),
+                                (-1.3088339518827734, -0.5173661350567303, 1.1597967522753032),
+                                (-2.23462275856269, 0.17332354052924734, -0.19455307765792382),
+                                (-1.393828440234405, 1.2294860794610234, 0.9656140588162426),
+                                (-0.12370667081323389, 1.0672740524773998, -1.1795070012935482),
+                                (-0.037324731014725374, -0.7080479312151163, -0.9821574183694773)),
+                     'isotopes': (12, 12, 16, 14, 16, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'O', 'N', 'O', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C2H5NO2', smiles='[O-][N+](=O)CC', xyz=c6h5_xyz)
+        p_1 = ARCSpecies(label='C2H5ONO', smiles='CCON=O', xyz=c7h5o_xyz)
+        rxn = ARCReaction(reactants=['C2H5NO2'], products=['C2H5ONO'],
+                          r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [4, 3, 2, 1, 0, 8, 9, 6, 5, 7])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Disproportionation: C4H7 + O2 <=> HO2 + C4H6
+        c4h7_xyz = {'coords': ((-2.040921404503424, -0.12903384637698798, 0.1559892045303822),
+                               (-0.7546540332943176, -0.4098957103161423, -0.07681407943731554),
+                               (0.3137517227573887, 0.47379064315829633, 0.303025839828397),
+                               (0.09502978026667419, 1.3942096052269417, 0.834199535314798),
+                               (1.734012668678617, 0.08135386277553083, 0.0906583073064836),
+                               (-2.352694765027891, 0.7875623110661275, 0.6465408489803196),
+                               (-2.8196259554078997, -0.8225020395029484, -0.14562281062524043),
+                               (-0.49241522029670126, -1.3423933663677394, -0.5719234920796793),
+                               (2.1384679029944533, -0.37774268314938586, 0.9976275308860051),
+                               (2.3331746195641365, 0.9677350359207318, -0.13953736233285224),
+                               (1.8458746842689961, -0.623083812434417, -0.7393520512375593)),
+                    'isotopes': (12, 12, 12, 1, 12, 1, 1, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'C', 'H', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c4h6_xyz = {'coords': ((-1.1313721520581368, 0.4375787725187425, 1.3741095482244203),
+                               (-0.5236696446754213, -0.27046339876338915, 0.4152401808417905),
+                               (0.5236696150303143, 0.2704633473040529, -0.41524017130113694),
+                               (1.1313721685204072, -0.4375787650279751, -1.3741095524658273),
+                               (-0.8696512779281117, 1.4694838181320669, 1.5851480041034802),
+                               (-1.915706463982211, -0.010750118295295768, 1.9758596362701513),
+                               (-0.8263303869083625, -1.301920739528746, 0.24674332317151054),
+                               (0.8263303006084768, 1.3019207019374226, -0.24674330995607902),
+                               (1.9157064555415753, 0.010750214228214268, -1.9758596165946158),
+                               (0.8696513858514865, -1.469483832503432, -1.5851480422945032)),
+                    'isotopes': (12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C4H7', smiles='C=C[CH]C', xyz=c4h7_xyz)
+        r_2 = ARCSpecies(label='O2', smiles='[O][O]', xyz=self.o2_xyz)
+        p_1 = ARCSpecies(label='HO2', smiles='O[O]', xyz=self.ho2_xyz)
+        p_2 = ARCSpecies(label='C4H6', smiles='C=CC=C', xyz=c4h6_xyz)
+        rxn = ARCReaction(reactants=['C4H7', 'O2'], products=['HO2', 'C4H6'],
+                          r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[:5], [3, 4, 5, 10, 6])
+        self.assertIn(rxn.atom_map[5:7], [[8, 7], [7, 8]])
+        self.assertEqual(rxn.atom_map[7], 9)
+        self.assertIn(tuple(rxn.atom_map[8:11]), permutations([2, 11, 12]))
+        self.assertIn(tuple(rxn.atom_map[11:]), permutations([0, 1]))
+
+        # Disproportionation: HO2 + NHOH <=> NH2OH + O2
+        nhoh_xyz = {'coords': ((0.5055094877826753, 0.03248552573561613, -0.443416250587286),
+                               (1.392367115364475, -0.021750569314658803, 0.07321920788090872),
+                               (-0.570163178752975, -0.035696714715839996, 0.48914535186936214),
+                               (-1.3277134243941644, 0.024961758294888944, -0.11894830916297996)),
+                    'isotopes': (14, 1, 16, 1), 'symbols': ('N', 'H', 'O', 'H')}
+        nh2oh_xyz = {'coords': ((-0.442357984214193, 0.12755746178283767, -0.283450834226086),
+                                (0.8066044298181865, -0.19499391813986608, 0.38695057103192726),
+                                (-0.9953709942529645, -0.7170738803381369, -0.11579136415085267),
+                                (-0.8349557675364339, 0.8418549600381088, 0.33540420712720587),
+                                (1.4660803161854115, -0.05734462334294334, -0.32311257978218827)),
+                     'isotopes': (14, 16, 1, 1, 1), 'symbols': ('N', 'O', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='NHOH', smiles='[NH]O', xyz=nhoh_xyz)
+        r_2 = ARCSpecies(label='HO2', smiles='O[O]', xyz=self.ho2_xyz)
+        p_1 = ARCSpecies(label='O2', smiles='[O][O]', xyz=self.o2_xyz)
+        p_2 = ARCSpecies(label='NH2OH', smiles='NO', xyz=nh2oh_xyz)
+        rxn = ARCReaction(reactants=['NHOH', 'HO2'], products=['O2', 'NH2OH'],
+                          r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[0], 2)
+        for index in [1, 6]:
+            self.assertIn(rxn.atom_map[index], [4, 5])
+        self.assertEqual(rxn.atom_map[2], 3)
+        self.assertEqual(rxn.atom_map[3], 6)
+        for index in [4, 5]:
+            self.assertIn(rxn.atom_map[index], [0, 1])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Intra_Disproportionation: C10H10_a <=> C10H10_b
+        c10h10_a_xyz = {'coords': ((3.1623638230700997, 0.39331289450005563, -0.031839117414963584),
+                                   (1.8784852381397288, 0.037685951926618944, -0.13659028131444134),
+                                   (0.9737380560194014, 0.5278617594060281, -1.1526858375270472),
+                                   (1.2607098516126556, 1.1809007875206383, -1.9621017164412065),
+                                   (-0.36396095305912823, -0.13214785064139675, -1.0200667625809143),
+                                   (-1.5172464644867296, 0.8364138939810618, -1.0669384323486588),
+                                   (-2.4922101649968655, 0.8316551483126366, -0.14124720277902958),
+                                   (-2.462598061982958, -0.09755474191953761, 0.9703503187569243),
+                                   (-1.4080417204047313, -0.8976377310686736, 1.1927020968566089),
+                                   (-0.27981087345916755, -0.8670643393461046, 0.29587765657632165),
+                                   (1.1395623815572733, -0.9147118621123697, 0.771368745020215),
+                                   (3.7901243915692864, -0.006544237180536178, 0.7580206603561134),
+                                   (3.6186251824572455, 1.0920401631166292, -0.725695658374561),
+                                   (-0.4799044636709365, -0.8577283498506146, -1.8345168113636874),
+                                   (-1.5704890060131314, 1.527002009812866, -1.902575985299536),
+                                   (-3.3260277144990296, 1.5238536460491903, -0.20338465526703625),
+                                   (-3.311126364299293, -0.09969554359088921, 1.6478137927333953),
+                                   (-1.3707042898204835, -1.549541647625315, 2.0589774409040964),
+                                   (1.5338362221707007, -1.9310023570889727, 0.6663504223502944),
+                                   (1.2246749300961473, -0.5970975942012858, 1.816181327157103)),
+                        'isotopes': (12, 12, 12, 1, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                        'symbols': ('C', 'C', 'C', 'H', 'C', 'C', 'C', 'C', 'C', 'C', 'C',
+                                    'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c10h10_b_xyz = {'coords': ((3.247237794328524, -0.13719671162966918, 0.19555833918937052),
+                                   (1.9094861712282774, -0.08067655688828143, 0.14898941432495702),
+                                   (0.9973729357914858, -1.2703386896415134, -0.09322848415119056),
+                                   (-0.37904449715218924, -0.6747166782032148, -0.049044448345326556),
+                                   (-0.32906812544096026, 0.704634441388649, 0.189424753183012),
+                                   (-1.4900181263846768, 1.4572613706024167, 0.2695747550348709),
+                                   (-2.715200996994148, 0.8069241052920498, 0.10660938013945513),
+                                   (-2.765284083663716, -0.5753713833636181, -0.13236922431004927),
+                                   (-1.5909002849280705, -1.3270914347507115, -0.21179882275795825),
+                                   (1.0862366144301145, 1.1823049698313937, 0.33079658088902575),
+                                   (3.8424769924852367, 0.7530758608805569, 0.37314678191170336),
+                                   (3.7762437608797406, -1.0749685445597326, 0.05710603017340202),
+                                   (1.1128196175313243, -2.0170485762246773, 0.6986324476157837),
+                                   (1.187449599052061, -1.7129398667445945, -1.0760419644685346),
+                                   (-1.453108430051206, 2.525963604437891, 0.45426129138400156),
+                                   (-3.639988653002051, 1.3756767310587803, 0.16518163487425436),
+                                   (-3.7283956370857467, -1.0643593255501977, -0.2566648708585298),
+                                   (-1.631427244782937, -2.3956407728893367, -0.3966116183664473),
+                                   (1.3188711462571718, 1.9143096670969255, -0.4489453399950017),
+                                   (1.2442414475018486, 1.6101977898569013, 1.3257284397785851)),
+                        'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                        'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C',
+                                    'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C10H10_a', smiles='C=C1[CH]C2C=CC=C[C]2C1', xyz=c10h10_a_xyz, multiplicity=3)
+        p_1 = ARCSpecies(label='C10H10_b', smiles='C=C1CC2=C(C=CC=C2)C1', xyz=c10h10_b_xyz)
+        rxn = ARCReaction(reactants=['C10H10_a'], products=['C10H10_b'],
+                          r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [0, 1, 8, 13, 3, 2, 7, 6, 5, 4, 9, 10, 17, 12, 11, 16, 15, 14, 19, 18])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Cyclopentadiene_scission: C6H6 <=> C6H6_2
+        c6h6_a_xyz = {'coords': ((1.465264096022479, 0.3555098886638667, 0.15268159347190322),
+                                 (0.4583546746026421, 1.1352991023740606, -0.26555553330413073),
+                                 (-0.7550043760214846, 0.35970165318809594, -0.5698935045151712),
+                                 (-1.485327813119871, -0.35660657095915016, 0.46119177830578917),
+                                 (-0.3414477960946828, -1.060779229397218, -0.11686056681841692),
+                                 (0.9879417277856641, -1.006839916409751, 0.12489717473407935),
+                                 (2.4630837864551887, 0.6629994259328668, 0.4197578798464181),
+                                 (0.5110882588097015, 2.2100951208919897, -0.3734820378556644),
+                                 (-1.1192886361027838, 0.384286081689225, -1.5897813181530946),
+                                 (-2.453224961870327, -0.7758708758357847, 0.2158838729688473),
+                                 (-1.3859013659398718, -0.054382091828296085, 1.4971154213962072),
+                                 (1.6544624054733257, -1.8534125883098933, 0.0440452399232336)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c6h6_b_xyz = {'coords': ((-1.474267041853848, 0.27665693719971857, -0.31815898666696507),
+                                 (-0.25527025747758825, 1.1936776717612125, -0.2432148642540069),
+                                 (0.9917471212521393, 0.7578589393970138, 0.059037260524552534),
+                                 (1.2911962562420976, -0.6524103892231805, 0.34598643264742923),
+                                 (0.321535921890914, -1.5867102018006056, 0.32000545365633654),
+                                 (-0.9417407846918554, -1.043897260224426, -0.002820356559266387),
+                                 (-2.2262364004658077, 0.5956762298613206, 0.40890113659975075),
+                                 (-1.90597332290244, 0.31143075666839354, -1.3222845692785703),
+                                 (-0.4221153027089989, 2.2469871640348815, -0.4470234892644997),
+                                 (1.824518548011024, 1.4543788790156666, 0.0987362566117616),
+                                 (2.3174577767359237, -0.9162726684959432, 0.5791638390925197),
+                                 (0.4791474859684761, -2.637376058194065, 0.5216718868909702)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C6H6_1', smiles='C1=CC2CC2=C1', xyz=c6h6_a_xyz)
+        p_1 = ARCSpecies(label='C6H6_b', xyz=c6h6_b_xyz, adjlist="""multiplicity 1
+                                                                    1  C u0 p0 c0 {2,S} {6,S} {7,S} {8,S}
+                                                                    2  C u0 p0 c0 {1,S} {3,D} {9,S}
+                                                                    3  C u0 p0 c0 {2,D} {4,S} {10,S}
+                                                                    4  C u0 p0 c0 {3,S} {5,D} {11,S}
+                                                                    5  C u0 p0 c0 {4,D} {6,S} {12,S}
+                                                                    6  C u0 p1 c0 {1,S} {5,S}
+                                                                    7  H u0 p0 c0 {1,S}
+                                                                    8  H u0 p0 c0 {1,S}
+                                                                    9  H u0 p0 c0 {2,S}
+                                                                    10 H u0 p0 c0 {3,S}
+                                                                    11 H u0 p0 c0 {4,S}
+                                                                    12 H u0 p0 c0 {5,S}""")
+        rxn = ARCReaction(reactants=['C6H6_1'], products=['C6H6_b'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [1, 4, 2, 0, 5, 3, 10, 9, 8, 7, 6, 11])
+        self.assertTrue(check_atom_map(rxn))
+
+        # intra_NO2_ONO_conversion: C2H5NO2 <=> C2H5ONO
+        c6h5_xyz = {'coords': ((1.8953828083622057, 0.8695975650550358, 0.6461465212661076),
+                               (1.3601473931706598, -0.04212583715410005, 0.0034200061443233247),
+                               (1.8529583069008781, -0.6310931351538215, -0.9666668585141432),
+                               (-0.010154355673379136, -0.4652844276756663, 0.43320585211058743),
+                               (-1.0281604639422022, 0.36855062612122236, -0.3158851121891869),
+                               (-0.11071296591935365, -1.5314728469286516, 0.20909234121344752),
+                               (-0.07635985361458197, -0.31625218083177237, 1.5151037167736001),
+                               (-2.042322710601489, 0.08102183703582924, -0.021667016484293297),
+                               (-0.9033569412063314, 1.436005790671757, -0.10388682333330314),
+                               (-0.937421217476434, 0.23105260886017234, -1.3988626269871478)),
+                    'isotopes': (16, 14, 16, 12, 12, 1, 1, 1, 1, 1),
+                    'symbols': ('O', 'N', 'O', 'C', 'C', 'H', 'H', 'H', 'H', 'H')}
+        c7h5o_xyz = {'coords': ((-1.3334725178745668, 0.2849178019354427, 0.4149005134933577),
+                                (-0.08765353373275289, 0.24941420749682627, -0.4497882845360618),
+                                (1.0488580188184402, 0.3986394744609146, 0.39515448276833964),
+                                (2.2292240798482883, 0.36629637181188207, -0.4124684043339001),
+                                (3.2413605054484185, 0.4928521621538312, 0.283008378837631),
+                                (-1.3088339518827734, -0.5173661350567303, 1.1597967522753032),
+                                (-2.23462275856269, 0.17332354052924734, -0.19455307765792382),
+                                (-1.393828440234405, 1.2294860794610234, 0.9656140588162426),
+                                (-0.12370667081323389, 1.0672740524773998, -1.1795070012935482),
+                                (-0.037324731014725374, -0.7080479312151163, -0.9821574183694773)),
+                     'isotopes': (12, 12, 16, 14, 16, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'O', 'N', 'O', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C2H5NO2', smiles='[O-][N+](=O)CC', xyz=c6h5_xyz)
+        p_1 = ARCSpecies(label='C2H5ONO', smiles='CCON=O', xyz=c7h5o_xyz)
+        rxn = ARCReaction(reactants=['C2H5NO2'], products=['C2H5ONO'],
+                          r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [4, 3, 2, 1, 0, 8, 9, 6, 5, 7])
+        self.assertTrue(check_atom_map(rxn))
+
+        # 1,2-Birad_to_alkene: SO2(T) => SO2(S)
+        # This test fails due to a problem in xyz perception of SO2(T).
+        so2_t_xyz = {'coords': ((0.02724478716956233, 0.6093829407458188, 0.0),
+                                (-1.3946381818031768, -0.24294788636871906, 0.0),
+                                (1.3673933946336125, -0.36643505437710233, 0.0)),
+                     'isotopes': (32, 16, 16), 'symbols': ('S', 'O', 'O')}
+        so2_s_xyz = {'coords': ((-1.3554230894998571, -0.4084942756329785, 0.0),
+                                (-0.04605352293144468, 0.6082507106551855, 0.0),
+                                (1.4014766124312934, -0.19975643502220325, 0.0)),
+                     'isotopes': (16, 32, 16), 'symbols': ('O', 'S', 'O')}
+
+        r_1 = ARCSpecies(label='SO2(T)', smiles='O=[S][O]', multiplicity=3, xyz=so2_t_xyz)
+        p_1 = ARCSpecies(label='SO2(S)', smiles='O=S=O', multiplicity=1, xyz=so2_s_xyz)
+        rxn = ARCReaction(reactants=['SO2(T)'], products=['SO2(S)'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map[0], 1)
+        self.assertTrue(check_atom_map(rxn))
+        # F[C]F + [CH3] <=> F[C](F)C
+        r1_xyz = {'symbols': ('F', 'C', 'F'),
+                  'isotopes': (19, 12, 19),
+                  'coords': ((-1.304203748543047, 0.3204330512721478, 0.0),
+                             (-1.9140293120972295e-09, -6.455569423898419e-09, 0.0),
+                             (1.304203750457077, -0.32043304481658, 0.0))}
+        r2_xyz = {'symbols': ('C', 'H', 'H', 'H'),
+                  'isotopes': (12, 1, 1, 1),
+                  'coords': ((3.3746019998564553e-09, 5.828827384106545e-09, -4.859105107686622e-09),
+                             (1.0669051052331406, -0.17519582095514982, 0.05416492980439295),
+                             (-0.6853171627400634, -0.8375353626879753, -0.028085652887100996),
+                             (-0.3815879458676787, 1.0127311778142964, -0.026079272058187608))}
+        p1_xyz = {'symbols': ('F', 'C', 'F', 'C', 'H', 'H', 'H'),
+                  'isotopes': (19, 12, 19, 12, 1, 1, 1),
+                  'coords': ((1.119619553527753, 1.4683016995266238, -0.4256355476700406),
+                             (0.7853078782246593, 0.21618941405118694, -0.04988462642839442),
+                             (1.7521918404307653, -0.6690180410121276, 0.2699297634217041),
+                             (-0.6404114764644544, -0.17821988481768988, 0.034782780206236624),
+                             (-0.7526348686344194, -1.2468644821661592, -0.16730131057453498),
+                             (-1.2335484316315908, 0.3780341245687702, -0.6961093474225755),
+                             (-1.0305244954526513, 0.03157716984946183, 1.0342182884675877))}
+        rxn = ARCReaction(r_species=[ARCSpecies(label="r1", smiles="F[C]F", xyz=r1_xyz),
+                                     ARCSpecies(label="r2", smiles="[CH3]", xyz=r2_xyz)],
+                          p_species=[ARCSpecies(label="p1", smiles="F[C](F)C", xyz=p1_xyz)])
+        self.assertIn(rxn.atom_map[:2], [[0, 1], [1, 0]])
+        self.assertEqual(rxn.atom_map[2], 2)
+        self.assertEqual(rxn.atom_map[3], 3)
+        self.assertIn(tuple(rxn.atom_map[4:]), list(permutations([4, 5, 6])))
+        self.assertTrue(check_atom_map(rxn))
+
+        # 1,2_NH3_elimination: NCC <=> C2H4 + NH3
+        ncc_xyz = {'coords': ((1.1517341397735719, -0.37601689454792764, -0.5230788502681245),
+                              (0.2893395715754821, 0.449973844025586, 0.3114935868175311),
+                              (-1.1415136758153028, -0.05605900830417449, 0.25915656466172177),
+                              (1.1385906595862103, -1.3375972344465683, -0.18540144244632334),
+                              (2.115146540825731, -0.05549033543399281, -0.4352422172888292),
+                              (0.6517228987651973, 0.4341829477365257, 1.3446618712379401),
+                              (0.32794656354609036, 1.4855039198343405, -0.04141588729000556),
+                              (-1.2132836539673237, -1.083868352883045, 0.6307611987658565),
+                              (-1.7869541982465666, 0.5726121409749625, 0.8809463351815471),
+                              (-1.5327288460430881, -0.03324102695569548, -0.763616120234416)),
+                   'isotopes': (14, 12, 12, 1, 1, 1, 1, 1, 1, 1),
+                   'symbols': ('N', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c2h4_xyz = {'coords': ((0.6664040429179742, 0.044298334171779405, -0.0050238049104911735),
+                               (-0.6664040438461246, -0.04429833352898575, 0.00502380522486473),
+                               (1.1686968388986039, 0.8743086488169786, -0.4919298928897832),
+                               (1.2813853343929593, -0.7114426553520238, 0.4734595111827543),
+                               (-1.2813853352424778, 0.7114426574294024, -0.4734595076873365),
+                               (-1.1686968371212578, -0.8743086515369692, 0.49192988907998186)),
+                    'isotopes': (12, 12, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'H', 'H', 'H', 'H')}
+        nh3_xyz = {'coords': ((0.0006492354002636227, -0.0009969784288894215, 0.2955929244020652),
+                              (-0.4178660616416419, 0.842103963871788, -0.09477452075659776),
+                              (-0.5203922802597125, -0.7822529247012627, -0.10002797449860866),
+                              (0.9376091065010891, -0.05885406074163403, -0.10079042914685925)),
+                   'isotopes': (14, 1, 1, 1),
+                   'symbols': ('N', 'H', 'H', 'H')}
+
+        r_1 = ARCSpecies(label='NCC', smiles='NCC', xyz=ncc_xyz)
+        p_1 = ARCSpecies(label='C2H4', smiles='C=C', xyz=c2h4_xyz)
+        p_2 = ARCSpecies(label='NH3', smiles='N', xyz=nh3_xyz)
+        rxn = ARCReaction(reactants=['NCC'], products=['C2H4', 'NH3'], r_species=[r_1], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[0], 6)
+        self.assertIn(rxn.atom_map[1:3], [[1, 0], [0, 1]])
+        self.assertIn(tuple(rxn.atom_map[3:5]+[rxn.atom_map[7]]), permutations([7, 8, 9]))
+        self.assertIn(tuple(rxn.atom_map[5:7]+rxn.atom_map[8:]), permutations([2, 3, 4, 5]))
+        self.assertTrue(check_atom_map(rxn))
+
+        # 1+2_Cycloaddition: CH2 + C2H4 <=> C3H6
+        c2h4_xyz = {'coords': ((0.6664040429179742, 0.044298334171779405, -0.0050238049104911735),
+                               (-0.6664040438461246, -0.04429833352898575, 0.00502380522486473),
+                               (1.1686968388986039, 0.8743086488169786, -0.4919298928897832),
+                               (1.2813853343929593, -0.7114426553520238, 0.4734595111827543),
+                               (-1.2813853352424778, 0.7114426574294024, -0.4734595076873365),
+                               (-1.1686968371212578, -0.8743086515369692, 0.49192988907998186)),
+                    'isotopes': (12, 12, 1, 1, 1, 1), 'symbols': ('C', 'C', 'H', 'H', 'H', 'H')}
+        c_c3h6_xyz = {'coords': ((0.7868661913782324, -0.3644249639827158, -0.016337299842911886),
+                                 (-0.07793785747147405, 0.8603229755261934, 0.07746513362297117),
+                                 (-0.708928275400647, -0.4958980792223481, -0.06112784358024908),
+                                 (1.339749295484817, -0.5278616711993785, -0.9341881111902739),
+                                 (1.3001119953298585, -0.6947493102195698, 0.8793780279658545),
+                                 (-0.15055582331881673, 1.3597070015370083, 1.0367271647162946),
+                                 (-0.11091839380255, 1.5265948517709569, -0.7768389650606503),
+                                 (-1.1693748373792934, -0.7484015319217499, -1.0093221066790388),
+                                 (-1.2090122948201234, -0.9152892722884018, 0.8042440000480116)),
+                      'isotopes': (12, 12, 12, 1, 1, 1, 1, 1, 1), 'symbols': ('C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+
+        r_1 = ARCSpecies(label='CH2', xyz=self.ch2_xyz, adjlist="""1 C u0 p1 c0 {2,S} {3,S}
+                                                                   2 H u0 p0 c0 {1,S}
+                                                                   3 H u0 p0 c0 {1,S}""")
+        r_2 = ARCSpecies(label='C2H4', smiles='C=C', xyz=c2h4_xyz)
+        p_1 = ARCSpecies(label='cC3H6', smiles='C1CC1', xyz=c_c3h6_xyz)
+        rxn = ARCReaction(reactants=['CH2', 'C2H4'], products=['cC3H6'], r_species=[r_1, r_2], p_species=[p_1])
+        for index in [0, 3, 4]:
+            self.assertIn(rxn.atom_map[index], [0, 1, 2])
+        for index in [1, 2, 5, 6, 7, 8]:
+            self.assertIn(rxn.atom_map[index], [3, 4, 5, 6, 7, 8])
+        self.assertTrue(check_atom_map(rxn))
+
+        # 1,2_Insertion_CO: C4H10 + CO <=> C5H10O
+        c4h10_xyz = {'coords': ((-0.5828455298013108, 1.3281531294599287, -0.04960015063595639),
+                                (0.20452033859928953, 0.05503751610159247, -0.351590668388836),
+                                (1.2187217734495472, -0.22435034939324036, 0.7553438935018645),
+                                (-0.7402757883531311, -1.131897259046642, -0.526270047908048),
+                                (-1.149632334529979, 1.2345299096044358, 0.8830543278319224),
+                                (-1.2910247691071444, 1.5474495198220646, -0.8556442099189145),
+                                (0.08958996004802251, 2.187049294072444, 0.047578963870699015),
+                                (0.7510696374695547, 0.20211678856476709, -1.2911649516059494),
+                                (1.9161788635733445, 0.6129834282608764, 0.8637033961259424),
+                                (0.723393227383255, -0.37955365746174813, 1.7199258030015812),
+                                (1.8052293751859985, -1.1207509229675587, 0.5277678765569422),
+                                (-1.4506401201091412, -0.9467671747910582, -1.3389353480864132),
+                                (-1.31330819789714, -1.3230974306153704, 0.3874767468986707),
+                                (-0.18097643591114793, -2.04090279161046, -0.7716456312435797)),
+                     'isotopes': (12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c5h10o_xyz = {'coords': ((1.4311352287218408, -0.1713595727440808, -0.4215888483848517),
+                                 (-0.007186117613478591, 0.06984820110647515, 0.04712543561838732),
+                                 (-0.9581449869575146, 0.0768516496023853, -1.153820345745391),
+                                 (-0.42459441572492335, -1.0196556708425513, 1.0398144790596706),
+                                 (-0.06395445555126768, 1.4459669990683603, 0.6988370467311186),
+                                 (-0.39842691952831133, 1.6544415349370807, 1.860895997103657),
+                                 (1.7538538399565853, 0.5988164487250668, -1.1317944597170102),
+                                 (1.5308761668570723, -1.1450780226312873, -0.9137377478255552),
+                                 (2.130467943093651, -0.145756780679422, 0.4221764324976206),
+                                 (-1.9882342251557934, 0.2821166362714845, -0.8400630940054319),
+                                 (-0.6807867076715277, 0.8517398665867646, -1.8779276281234922),
+                                 (-0.9490513003000888, -0.8874499123119038, -1.6737493906621435),
+                                 (0.23329847490706446, -1.0315570674753483, 1.9164599735169805),
+                                 (-0.3863240121264062, -2.0126378831961222, 0.578337115559457),
+                                 (-1.4463966539332702, -0.8570614833514035, 1.4016914821743647),
+                                 (0.22346814102625032, 2.2907750569345855, 0.04734355220249537)),
+                      'isotopes': (12, 12, 12, 12, 12, 16, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'O', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C4H10', smiles='CC(C)C', xyz=c4h10_xyz)
+        r_2 = ARCSpecies(label='CO', smiles='[C-]#[O+]', xyz=self.co_xyz)
+        p_1 = ARCSpecies(label='C5H10O', smiles='CC(C)(C)C=O', xyz=c5h10o_xyz)
+        rxn = ARCReaction(reactants=['C4H10', 'CO'], products=['C5H10O'],
+                          r_species=[r_1, r_2], p_species=[p_1])
+        atom_map = rxn.atom_map
+        self.assertEqual(atom_map[:4], [0, 1, 2, 3])
+        self.assertIn(tuple(rxn.atom_map[4:7]), permutations([6, 7, 8]))
+        self.assertEqual(atom_map[7], 15)
+        self.assertIn(tuple(rxn.atom_map[8:11]), permutations([9, 10, 11]))
+        self.assertIn(tuple(rxn.atom_map[11:14]), permutations([12, 13, 14]))
+        self.assertEqual(atom_map[14:], [4, 5])
+        self.assertTrue(check_atom_map(rxn))
+        # same reaction in reverse:
+        rxn_rev = ARCReaction(r_species=[p_1], p_species=[r_1, r_2])
+        atom_map = rxn_rev.atom_map
+        for index in [0, 2, 3]:
+            self.assertIn(atom_map[index], [0, 2, 3])
+        self.assertEqual(atom_map[1], 1)
+        self.assertEqual(atom_map[4], 14)
+        self.assertEqual(atom_map[5], 15)
+        self.assertEqual(atom_map[15], 7)
+        self.assertTrue(check_atom_map(rxn_rev))
+
+        # Diels_alder_addition: C5H8 + C6H10 <=> C11H18
+        c5h8_xyz = {'coords': ((2.388426506127341, -0.6020682478448856, -0.8986239521455471),
+                               (1.396815470095451, 0.2559764141247285, -0.632876393172657),
+                               (0.15313289103802616, -0.14573699483201027, -0.021031021618524288),
+                               (-0.8389550397179193, 0.7169723970589436, 0.24404493146763848),
+                               (-2.134416163598417, 0.3239681447826502, 0.876570575233924),
+                               (2.3152942675091053, -1.659966892807757, -0.6677097540505594),
+                               (3.307483005086718, -0.2549641760041707, -1.3602353900805908),
+                               (1.5244650427331894, 1.3064325129702357, -0.885889345476673),
+                               (0.03466763777311284, -1.1983886005211812, 0.22843510909849465),
+                               (-0.7292165776910954, 1.7707854265126919, -0.0018778749819206306),
+                               (-2.2727957408233483, 0.8723614467877541, 1.8133393569164875),
+                               (-2.964923876317021, 0.5697550629604972, 0.20779128725191479),
+                               (-2.179977422215191, -0.7469982986693162, 1.0980624715582143)),
+                    'isotopes': (12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c6h10_xyz = {'coords': ((-3.1580683741393027, 0.12435732050743648, 0.062246914825226686),
+                                (-1.7707067002277326, -0.16620360178113405, 0.5349691635238483),
+                                (-0.6661431116320429, 0.14509293595419076, -0.15922278773395507),
+                                (0.6661430871150528, -0.14509454337155672, 0.31675535258860427),
+                                (1.7707067221399997, 0.1662031310249801, -0.37743578397831457),
+                                (3.158068300764984, -0.1243566042028104, 0.0952878105284522),
+                                (-3.168673040679144, 0.6195109523415628, -0.9138744940397917),
+                                (-3.725598607890039, -0.8074661408951581, -0.02161915764945937),
+                                (-3.667502866324593, 0.7743593207314634, 0.7801554985274884),
+                                (-1.689979340654408, -0.658941962521633, 1.5012451075034898),
+                                (-0.7566435422183935, 0.638020444531764, -1.1251628620848497),
+                                (0.7566435677358615, -0.6380221416323665, 1.2826952112274577),
+                                (1.6899798722782449, 0.6589420540549689, -1.3437113386443575),
+                                (3.667504053415929, -0.7743586338884942, -0.6226199722740314),
+                                (3.168672421569792, -0.6195094502282033, 1.0714098656973499),
+                                (3.7255975587458146, 0.8074669193750107, 0.17915450597834431)),
+                     'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c11h18_xyz = {'coords': ((-2.703705731925332, -1.6725650155987697, -0.8086740370494231),
+                                 (-1.5787486719767332, -0.9567028627407828, -0.9374280026568313),
+                                 (-1.0380952176862677, -0.018956959638684944, 0.13044184610143217),
+                                 (-0.9559942521379576, 1.4339345435700377, -0.4211901270741127),
+                                 (-1.0332585693389826, 2.4699679588763424, 0.7057994083773913),
+                                 (0.29330767863777807, 1.6799654965887798, -1.231863983890581),
+                                 (1.3587533124739988, 0.8659977820300574, -1.2254134762392683),
+                                 (1.4646089005142253, -0.38325835216422677, -0.38135979446817597),
+                                 (2.8541328762948206, -0.44094297285873296, 0.26496359509221906),
+                                 (0.34006414566475085, -0.47702332337899384, 0.6874327625078416),
+                                 (0.25971352010871435, -1.877767868723041, 1.3110012371667645),
+                                 (-3.0417827308140666, -2.322041441265777, -1.6103599735778764),
+                                 (-3.3090907216942607, -1.6304164329807997, 0.09119562710875757),
+                                 (-1.0140304257321437, -1.0355853116087828, -1.8648599111730466),
+                                 (-1.7519605248870382, -0.02119386222025415, 0.9668436940879309),
+                                 (-1.81873965484405, 1.6086866163315763, -1.078721360123664),
+                                 (-1.0435582627465962, 3.4878991458476953, 0.2994048809648787),
+                                 (-1.951192645793586, 2.339835712359188, 1.2889715104672264),
+                                 (-0.1829564138869207, 2.3964873273832725, 1.392011686068868),
+                                 (0.30323343644376083, 2.563802985828772, -1.8662760923115096),
+                                 (2.19957127963344, 1.1019579368769516, -1.875167073357893),
+                                 (1.38566629304311, -1.2380356901050797, -1.0661633096552972),
+                                 (3.643719857910847, -0.3537387754651392, -0.49036436481236706),
+                                 (2.9928305557668415, 0.3709281222195243, 0.9878133651866298),
+                                 (3.0131256633168944, -1.3901032201204848, 0.7853911163504533),
+                                 (0.5952865875235361, 0.20718050090958492, 1.5092530947735325),
+                                 (-0.5854224393429074, -1.9456691543733, 2.004496412992174),
+                                 (1.163930543826011, -2.107144483058995, 1.883011771518183),
+                                 (0.1405916116476466, -2.6554984025201795, 0.5498094976254133)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,
+                                   1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'H',
+                                  'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C5H8', smiles='C=CC=CC', xyz=c5h8_xyz)
+        r_2 = ARCSpecies(label='C6H10', smiles='CC=CC=CC', xyz=c6h10_xyz)
+        p_1 = ARCSpecies(label='C11H18', smiles='C=CC1C(C)C=CC(C)C1C', xyz=c11h18_xyz)
+        rxn = ARCReaction(reactants=['C5H8', 'C6H10'], products=['C11H18'], r_species=[r_1, r_2], p_species=[p_1])
+        atom_map = rxn.atom_map
+        self.assertEqual(atom_map[:5], [0, 1, 2, 9, 10])
+        self.assertEqual(atom_map[:5], [0, 1, 2, 9, 10])
+        self.assertIn(atom_map[5:7], [[11, 12], [12, 11]])
+        self.assertEqual(atom_map[7:10], [13, 14, 25])
+        self.assertIn(tuple(rxn.atom_map[10:13]), permutations([26, 27, 28]))
+        self.assertEqual(atom_map[13:19], [8, 7, 6, 5, 3, 4])
+        self.assertIn(tuple(rxn.atom_map[19:22]), permutations([24, 23, 22]))
+        self.assertEqual(atom_map[22:26], [21, 20, 19, 15])
+        self.assertIn(tuple(rxn.atom_map[26:]), permutations([16, 17, 18]))
+        self.assertTrue(check_atom_map(rxn))
+
+        # Intra_R_Add_Endocyclic: C9H15_a <=> C9H15_b
+        c9h15_a_xyz = {'coords': ((3.2994642637411093, -0.9763218631003405, -0.6681519125224107),
+                                  (2.092867397835492, -0.585345209944081, -1.094234941414971),
+                                  (1.1613654936979811, 0.23706312530825574, -0.350374400298155),
+                                  (1.4994958941811034, 0.8089206946686178, 0.9907635052181555),
+                                  (-0.2167854131709981, 0.47662057541684727, -0.9114032766325476),
+                                  (-1.2860618884154418, -0.32193095884739475, -0.1923953058559322),
+                                  (-1.2894939032313453, -1.8000285883092857, -0.4999462913608906),
+                                  (-2.2130886752718024, 0.1935684936507141, 0.6410238159619941),
+                                  (-2.383413365750594, 1.6157044776486373, 1.0712910920067213),
+                                  (3.696965023185511, -0.7025114561770845, 0.3028336703297904),
+                                  (3.9271105560154953, -1.5992344159626835, -1.2980759074189403),
+                                  (1.7682570069194234, -0.916244398055435, -2.0798789408635727),
+                                  (2.487309562171708, 1.280610628494466, 0.9837303428781683),
+                                  (1.4864744914143402, 0.025765724669991667, 1.7553223060895524),
+                                  (0.7820729499500115, 1.5805317186266579, 1.2867175051786177),
+                                  (-0.4230089341260823, 1.5513883408081797, -0.8834461827090913),
+                                  (-0.2525088519499385, 0.22261243999961292, -1.9790204993055305),
+                                  (-1.3684387790718693, -1.963416003052446, -1.5797964159431177),
+                                  (-2.1302956103647683, -2.3198259338415648, -0.028168861405248807),
+                                  (-0.3695265066561803, -2.2717068331186607, -0.14091188769329688),
+                                  (-2.9423489352590817, -0.48429745146049047, 1.0846035398328122),
+                                  (-1.6122780147641311, 2.2876041556921556, 0.691039744143378),
+                                  (-3.355397325714956, 1.9889012668068031, 0.7341417908661508),
+                                  (-2.358736435364993, 1.6715714700786672, 2.1643375109183345)),
+                       'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                       'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H',
+                                   'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c9h15_b_xyz = {'coords': ((-2.5844283571790947, -1.0321735590817163, 0.6979015062994665),
+                                  (-1.7475791961733325, -0.06626031223098465, 1.0969062210689708),
+                                  (-0.6595890997866395, 0.44535980204779074, 0.19328352629720955),
+                                  (-1.2282980470691727, 1.3553131311426074, -0.9035809147486576),
+                                  (0.5116680348286848, 1.1207407424824027, 0.9673543663680071),
+                                  (1.4515588336620284, 0.3272984970368279, 0.15908291396837426),
+                                  (2.790359263734144, -0.07794911282678396, 0.6402051576162312),
+                                  (0.39868762752392606, -0.6378444769932384, -0.22420607008722174),
+                                  (0.4638588895257082, -1.0921494216349954, -1.67271225417489),
+                                  (-3.3702037268621954, -1.3885510696474426, 1.3571613514582264),
+                                  (-2.514756820219243, -1.4880585713706647, -0.2847299130808078),
+                                  (-1.8525509876151718, 0.37468306283449787, 2.084629086686036),
+                                  (-1.799839887685193, 2.183429924439949, -0.4685383552676342),
+                                  (-0.4353196261713602, 1.7968012774608193, -1.5175814720438623),
+                                  (-1.8935148835851774, 0.8013551257352, -1.5751801294655083),
+                                  (0.5782060423798034, 0.8980837541669382, 2.0389365697505366),
+                                  (0.6148811498579635, 2.2012663914014428, 0.8270631269396428),
+                                  (3.3879992933324807, 0.8037689675842231, 0.889705284982396),
+                                  (2.714060940989492, -0.70739197884347, 1.5320182978132968),
+                                  (3.3202001915969395, -0.6394149338748517, -0.13488149851161066),
+                                  (0.41364799755952236, -1.5167424973440258, 0.43811504056239386),
+                                  (0.5615949640204292, -0.25426187677410833, -2.3707422632792787),
+                                  (-0.44004933907211424, -1.649313877420301, -1.9393981990380054),
+                                  (1.3194067424075275, -1.7579889882901385, -1.8308113801134083)),
+                       'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                       'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H',
+                                   'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C9H15_a', smiles='C=C[C](C)CC(C)=CC', xyz=c9h15_a_xyz)
+        p_1 = ARCSpecies(label='C9H15_b', smiles='C=CC1(C)C[C](C)C1C', xyz=c9h15_b_xyz)
+        rxn = ARCReaction(reactants=['C9H15_a'], products=['C9H15_b'],
+                          r_species=[r_1], p_species=[p_1])
+        atom_map = rxn.atom_map
+        self.assertEqual(atom_map[0:9], list(range(9)))
+        self.assertIn(atom_map[9:11], [[9, 10], [10, 9]])
+        self.assertEqual(atom_map[11], 11)
+        self.assertIn(tuple(rxn.atom_map[12:15]), permutations([13, 14, 12]))
+        self.assertIn(atom_map[15:17], [[15, 16], [16, 15]])
+        self.assertIn(tuple(rxn.atom_map[17:20]), permutations([18, 17, 19]))
+        self.assertEqual(atom_map[20], 20)
+        self.assertIn(tuple(rxn.atom_map[21:]), permutations([23, 21, 22]))
+        self.assertTrue(check_atom_map(rxn))
+
+        # R_Addition_COm: C6H5 + CO <=> C7H5O
+        c6h5_xyz = {'coords': ((0.1817676212163122, -1.6072341699404684, -0.014610043584505971),
+                               (1.3027386938520413, -0.7802649159703986, -0.0076490984025043415),
+                               (1.1475642728457944, 0.6058877336062989, 0.0049505291900821605),
+                               (-0.13153090866637432, 1.1630287566213553, 0.010572132054881396),
+                               (-1.2538945539777469, 0.33431084106618875, 0.0035960198829159064),
+                               (-1.0955796250821246, -1.0514866492107922, -0.009001872474708414),
+                               (2.2945290976411314, -1.222259069017827, -0.0120983109779029),
+                               (2.0221784174097133, 1.2509576921755168, 0.010380274196135802),
+                               (-0.25367929671488426, 2.243094989267151, 0.020390170037011494),
+                               (-2.250483228275848, 0.767769623706613, 0.007970374795096042),
+                               (-1.9636104902480103, -1.7038048323036503, -0.014500174716503693)),
+                    'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H')}
+        c7h5o_xyz = {'coords': ((3.6046073677554133, -0.5344883784336433, -0.4686416595112313),
+                                (2.450376918247941, -0.36333993603429526, -0.3185783842705891),
+                                (1.0452654391924683, -0.1549911825981301, -0.13589722616572933),
+                                (0.17928460434727675, -1.2499432760163112, -0.05142261213479038),
+                                (-1.1903765403115871, -1.0453466445053263, 0.1266843926255701),
+                                (-1.6956393825954146, 0.2514281313346147, 0.22045344560169716),
+                                (-0.83456152850501, 1.3456029168509482, 0.13658183163326776),
+                                (0.5355376113902255, 1.1439499192771787, -0.04151298496012599),
+                                (0.5636535723209614, -2.2654604192056556, -0.12342236998627074),
+                                (-1.863668502126327, -1.8967496276402949, 0.19236058875963039),
+                                (-2.762672022813616, 0.4096470069241553, 0.3591803505729345),
+                                (-1.2308445290855283, 2.355601612430931, 0.2099632744051463),
+                                (1.1990369921831652, 2.0040898776158196, -0.1057486465694942)),
+                     'isotopes': (16, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1),
+                     'symbols': ('O', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C6H5', smiles='[c]1ccccc1', xyz=c6h5_xyz)
+        r_2 = ARCSpecies(label='CO', smiles='[C-]#[O+]', xyz=self.co_xyz)
+        p_1 = ARCSpecies(label='C7H5O', smiles='O=[C]c1ccccc1', xyz=c7h5o_xyz)
+        rxn = ARCReaction(reactants=['C6H5', 'CO'], products=['C7H5O'],
+                          r_species=[r_1, r_2], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 0])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Keto-enol isomerization: ch2choh <=> ch3cho
+        r_1 = ARCSpecies(label='CH2CHOH', smiles='C=CO', xyz=self.ch2choh_xyz)
+        p_1 = ARCSpecies(label='CH3CHO', smiles='CC=O', xyz=self.ch3cho_xyz)
+        rxn = ARCReaction(r_species=[r_1], p_species=[p_1])
+        atom_map = rxn.atom_map
+        self.assertTrue(check_atom_map(rxn))
+        self.assertTrue(atom_map[:3], [0, 1, 2])
+        self.assertIn(tuple(atom_map[3:5]+[atom_map[-1]]), permutations([3, 4, 5]))
+        self.assertEqual(atom_map[5], 6)
+
+    # Same species in products
+        rxn = ARCReaction(r_species=[ARCSpecies(label="r", smiles = 'C=C[CH]CC[CH]C=C')],
+                          p_species=[ARCSpecies(label="p1", smiles= 'C=CC=C'),
+                                     ARCSpecies(label="p2", smiles= 'C=CC=C')])
+        c_symmetry_h_1 = [1, 2, 11, 12]            # symmetry of carbons with one hydrogen
+        c_symmetry_h_2 = [0, 3, 10, 13]            # symmetry of carbons with two hydrogens
+        h_symmetry1 = [6, 7, 16, 17]               # symmetry of hydrogens with one other hydrogen second order neighbor
+        h_symmetry2 = [4, 5, 8, 9, 14 ,15, 18, 19] # symmetry of hydrogens with two other hydrogen second order neighbor
+        
+        label_species_atoms(rxn.r_species)
+        atom_map = rxn.atom_map
+        for atom in rxn.r_species[0].mol.copy(deep=True).atoms:
+            if atom.symbol == "C":
+                relevant_atom = atom
+            else:
+                relevant_atom = list(atom.bonds.keys())[0]
+            number_of_hydrogens = 0
+            for neighbor in relevant_atom.bonds.keys():
+                if neighbor.symbol=="H":
+                    number_of_hydrogens+=1
+            if number_of_hydrogens == 1:
+                self.assertIn(atom_map[int(atom.label)], c_symmetry_h_1 if atom.symbol == "C" else h_symmetry1)
+            else:
+                self.assertIn(atom_map[int(atom.label)], c_symmetry_h_2 if atom.symbol == "C" else h_symmetry2)
+        self.assertTrue(check_atom_map(rxn=rxn))
+
+    def test_mapping_XY_elimination_hydroxyl(self):
+        """Test mapping of a reaction family XY_elimination_hydroxyl"""    
+        rxn = ARCReaction(r_species=[ARCSpecies(label="r", smiles = 'O=C(O)CCF')],
+                          p_species=[ARCSpecies(label="p1", smiles='C=C'),
+                                     ARCSpecies(label="p2", smiles="F"),
+                                     ARCSpecies(label="p3", smiles="O=C=O")])
+        # if not rxn.family:  # reaction family not found for some reason.
+        #     rxn.family = "XY_elimination_hydroxyl"
+        atom_map = rxn.atom_map
+        self.assertIsNotNone(rxn.family)
+        self.assertTrue(check_atom_map(rxn=rxn))
+        self.assertIn(atom_map[:3], [[8, 9, 10], [10, 9, 8]])
+        self.assertIn(atom_map[3:5], [[0, 1], [1, 0]])
+        self.assertEqual(atom_map[5:7], [6, 7])
+        self.assertIn(atom_map[7:9], [[4, 5], [5, 4]])
+        self.assertIn(atom_map[9:], [[2, 3], [3, 2]])
+
+    def test_get_reactants_xyz(self):
+        """Test getting a combined string/dict representation of the cartesian coordinates of all reactant species"""
+        ch3nh2_xyz = {'coords': ((-0.5734111454228507, 0.0203516083213337, 0.03088703933770556),
+                                 (0.8105595891860601, 0.00017446498908627427, -0.4077728757313545),
+                                 (-1.1234549667791063, -0.8123899006368857, -0.41607711106038836),
+                                 (-0.6332220120842996, -0.06381791823047896, 1.1196983583774054),
+                                 (-1.053200912106195, 0.9539501896695028, -0.27567270246542575),
+                                 (1.3186422395164141, 0.7623906284020254, 0.038976118645639976),
+                                 (1.2540872076899663, -0.8606590725145833, -0.09003882710357966)),
+                      'isotopes': (12, 14, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'N', 'H', 'H', 'H', 'H', 'H')}
+        ch2nh2_xyz = {'coords': ((0.6919493009211066, 0.054389375309083846, 0.02065422596281878),
+                                 (1.3094508022837807, -0.830934909576592, 0.14456347719459348),
+                                 (1.1649142139806816, 1.030396183273415, 0.08526955368597328),
+                                 (-0.7278194451655412, -0.06628299353512612, -0.30657582460750543),
+                                 (-1.2832757211903472, 0.7307667658607352, 0.00177732009031573),
+                                 (-1.155219150829674, -0.9183344213315149, 0.05431124767380799)),
+                      'isotopes': (12, 1, 1, 14, 1, 1),
+                      'symbols': ('C', 'H', 'H', 'N', 'H', 'H')}
+        r_1 = ARCSpecies(label='H', smiles='[H]', xyz={'coords': ((0, 0, 0),), 'isotopes': (1,), 'symbols': ('H',)})
+        r_2 = ARCSpecies(label='CH3NH2', smiles='CN', xyz=ch3nh2_xyz)
+        p_1 = ARCSpecies(label='H2', smiles='[H][H]', xyz=self.h2_xyz)
+        p_2 = ARCSpecies(label='CH2NH2', smiles='[CH2]N', xyz=ch2nh2_xyz)
+        rxn_1 = ARCReaction(reactants=['H', 'CH3NH2'], products=['H2', 'CH2NH2'],
+                            r_species=[r_1, r_2], p_species=[p_1, p_2])
+        reactants_xyz_str = rxn_1.get_reactants_xyz()
+        reactants_xyz_dict = rxn_1.get_reactants_xyz(return_format='dict')
+        expected_reactants_xyz_str = """H      -0.33027713    0.00000000    0.00000000
+C      -0.69896689    0.01307198    0.19065646
+N       0.68500384   -0.00710516   -0.24800345
+H      -1.24901071   -0.81966953   -0.25630769
+H      -0.75877776   -0.07109755    1.27946778
+H      -1.17875666    0.94667056   -0.11590328
+H       1.19308649    0.75511100    0.19874554
+H       1.12853146   -0.86793870    0.06973060"""
+        expected_reactants_xyz_dict = {'symbols': ('H', 'C', 'N', 'H', 'H', 'H', 'H', 'H'),
+                                       'isotopes': (1, 12, 14, 1, 1, 1, 1, 1),
+                                       'coords': ((-0.33027712709756146, 0.0, 0.0),
+                                                  (-0.6989668914012913, 0.013071980537625375, 0.19065646408548476),
+                                                  (0.6850038432076193, -0.007105162794622051, -0.24800345098357532),
+                                                  (-1.2490107127575472, -0.8196695284205939, -0.25630768631260914),
+                                                  (-0.7587777580627403, -0.07109754601418727, 1.2794677831251846),
+                                                  (-1.1787566580846358, 0.9466705618857946, -0.11590327771764654),
+                                                  (1.1930864935379735, 0.7551110006183172, 0.19874554339341918),
+                                                  (1.1285314617115254, -0.8679387002982916, 0.06973059764419955))}
+        self.assertEqual(reactants_xyz_str, expected_reactants_xyz_str)
+        self.assertEqual(reactants_xyz_dict, expected_reactants_xyz_dict)
+
+        c2h5o3_xyz = {'coords': ((-1.3476727508427788, -0.49923624257482285, -0.3366372557370102),
+                                 (-0.11626816111736853, 0.3110915299407186, 0.018860985632263887),
+                                 (0.7531175607750088, 0.3366822240291409, -1.1050387236863213),
+                                 (0.5228736844989644, -0.3049881931104616, 1.1366016759286774),
+                                 (1.8270658637404131, 0.34102014147584997, 1.2684162942337813),
+                                 (-2.039181700362481, -0.5535509846570477, 0.5100031541057821),
+                                 (-1.865025875161301, -0.06806929272376178, -1.1994046923960628),
+                                 (-1.0711960095793496, -1.5264629385419055, -0.6002175107608478),
+                                 (-0.40133538695862053, 1.3357900487643664, 0.28224155088545305),
+                                 (1.3942569570346546, 1.035594500292526, -0.8890721851777293)),
+                      'isotopes': (12, 12, 16, 16, 16, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'O', 'O', 'O', 'H', 'H', 'H', 'H', 'H')}
+        c2h4o_xyz = {'coords': ((-0.6485165220711699, -0.036287809639473964, -0.040072327958319325),
+                                (0.8441328059817381, 0.04088405476411104, 0.05352861712992162),
+                                (1.4799812732494606, 1.0748679945888888, -0.1224478071645769),
+                                (-1.0603388058764294, 0.9464876376852732, -0.28238370478893315),
+                                (-0.9213427138232859, -0.7478396768473443, -0.8228167900899559),
+                                (-1.0499663443190728, -0.37234114306362315, 0.9187474043028493),
+                                (1.3560503068587568, -0.9057710574878411, 0.29544460856901716)),
+                     'isotopes': (12, 12, 16, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'O', 'H', 'H', 'H', 'H')}
+        ho2_xyz = {'coords': ((0.0558910, -0.6204870, 0.0000000),
+                              (0.0558910, 0.7272050, 0.0000000),
+                              (-0.8942590, -0.8537420, 0.0000000)),
+                   'isotopes': (16, 16, 1),
+                   'symbols': ('O', 'O', 'H')}
+        r_1 = ARCSpecies(label='C2H5O3', smiles='CC(O)O[O]', xyz=c2h5o3_xyz)
+        p_1 = ARCSpecies(label='C2H4O', smiles='CC=O', xyz=c2h4o_xyz)
+        p_2 = ARCSpecies(label='HO2', smiles='O[O]', xyz=ho2_xyz)
+        rxn = ARCReaction(r_species=[r_1], p_species=[p_1, p_2])
+        self.assertIn(rxn.atom_map[0:5], [[0, 1, 2, 8, 7], [0, 1, 2, 7, 8]])
+        for index in [5, 6, 7]:
+            self.assertIn(rxn.atom_map[index], [3, 4, 5])
+        self.assertEqual(rxn.atom_map[8], 6)
+        self.assertEqual(rxn.atom_map[9], 9)
+        self.assertTrue(check_atom_map(rxn))
+
+    def test_get_single_mapped_product_xyz(self):
+        """Test the Reaction get_single_mapped_product_xyz() method"""
+        # Trivial unimolecular with an intentional mixed atom order: H2O <=> H2O
+        h2o_xyz_1 = """O      -0.00032832    0.39781490    0.00000000
+                       H      -0.76330345   -0.19953755    0.00000000
+                       H       0.76363177   -0.19827735    0.00000000"""
+        r_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_1)
+        h2o_xyz_2 = """H      -0.76330345   -0.19953755    0.00000000
+                       H       0.76363177   -0.19827735    0.00000000
+                       O      -0.00032832    0.39781490    0.00000000"""
+        p_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_2)
+        rxn_1 = ARCReaction(reactants=['H2O'], products=['H2O'],
+                            r_species=[r_1], p_species=[p_1])
+        mapped_product = rxn_1.get_single_mapped_product_xyz()
+        self.assertEqual(rxn_1.atom_map, [2, 0, 1])
+        self.assertTrue(check_atom_map(rxn_1))
+        expected_xyz = {'symbols': ('O', 'H', 'H'), 'isotopes': (16, 1, 1),
+                        'coords': ((-0.00032832, 0.3978149, 0.0), (-0.76330345, -0.19953755, 0.0),
+                                   (0.76363177, -0.19827735, 0.0))}
+        self.assertEqual(mapped_product.get_xyz(), expected_xyz)
+
+        reactant_xyz = """C  -1.3087    0.0068    0.0318
+                          C   0.1715   -0.0344    0.0210
+                          N   0.9054   -0.9001    0.6395
+                          O   2.1683   -0.5483    0.3437
+                          N   2.1499    0.5449   -0.4631
+                          N   0.9613    0.8655   -0.6660
+                          H  -1.6558    0.9505    0.4530
+                          H  -1.6934   -0.0680   -0.9854
+                          H  -1.6986   -0.8169    0.6255"""
+        reactant = ARCSpecies(label='reactant', smiles='C([C]1=[N]O[N]=[N]1)', xyz=reactant_xyz)
+        product_xyz = """C  -1.0108   -0.0114   -0.0610
+                         C   0.4780    0.0191    0.0139
+                         N   1.2974   -0.9930    0.4693
+                         O   0.6928   -1.9845    0.8337
+                         N   1.7456    1.9701   -0.6976
+                         N   1.1642    1.0763   -0.3716
+                         H  -1.4020    0.9134   -0.4821
+                         H  -1.3327   -0.8499   -0.6803
+                         H  -1.4329   -0.1554    0.9349"""
+        product = ARCSpecies(label='product', smiles='[N-]=[N+]=C(N=O)C', xyz=product_xyz)
+        rxn_2 = ARCReaction(r_species=[reactant], p_species=[product])
+        self.assertTrue(check_atom_map(rxn_2))
+        mapped_product = rxn_2.get_single_mapped_product_xyz()
+        self.assertEqual(rxn_2.atom_map[:6], [0, 1, 2, 3, 4, 5])
+        self.assertIn(rxn_2.atom_map[6], [6, 8])
+        self.assertIn(rxn_2.atom_map[7], [6, 7])
+        self.assertIn(rxn_2.atom_map[8], [7, 8])
+        expected_xyz = {'symbols': ('C', 'C', 'N', 'O', 'N', 'N', 'H', 'H', 'H'),
+                        'isotopes': (12, 12, 14, 16, 14, 14, 1, 1, 1),
+                        'coords': ((-1.0108, -0.0114, -0.061), (0.478, 0.0191, 0.0139), (1.2974, -0.993, 0.4693),
+                                   (0.6928, -1.9845, 0.8337), (1.7456, 1.9701, -0.6976), (1.1642, 1.0763, -0.3716),
+                                   (-1.4329, -0.1554, 0.9349), (-1.402, 0.9134, -0.4821), (-1.3327, -0.8499, -0.6803))}
+        self.assertEqual(mapped_product.get_xyz(), expected_xyz)
+
+        reactant_xyz = """C  -1.3087    0.0068    0.0318
+                          C   0.1715   -0.0344    0.0210
+                          N   0.9054   -0.9001    0.6395
+                          O   2.1683   -0.5483    0.3437
+                          N   2.1499    0.5449   -0.4631
+                          N   0.9613    0.8655   -0.6660
+                          H  -1.6558    0.9505    0.4530
+                          H  -1.6934   -0.0680   -0.9854
+                          H  -1.6986   -0.8169    0.6255"""
+        reactant = ARCSpecies(label='reactant', smiles='C([C]1=[N]O[N]=[N]1)', xyz=reactant_xyz)
+        product_xyz = """C  -1.0108   -0.0114   -0.0610
+                         C   0.4780    0.0191    0.0139
+                         N   1.2974   -0.9930    0.4693
+                         O   0.6928   -1.9845    0.8337
+                         N   1.7456    1.9701   -0.6976
+                         N   1.1642    1.0763   -0.3716
+                         H  -1.4020    0.9134   -0.4821
+                         H  -1.3327   -0.8499   -0.6803
+                         H  -1.4329   -0.1554    0.9349"""
+        product = ARCSpecies(label='product', smiles='[N-]=[N+]=C(N=O)C', xyz=product_xyz)
+        rxn_2 = ARCReaction(r_species=[reactant], p_species=[product])
+        self.assertTrue(check_atom_map(rxn_2))
+        mapped_product = rxn_2.get_single_mapped_product_xyz()
+        self.assertEqual(rxn_2.atom_map[:6], [0, 1, 2, 3, 4, 5])
+        self.assertIn(rxn_2.atom_map[6], [6, 8])
+        self.assertIn(rxn_2.atom_map[7], [6, 7])
+        self.assertIn(rxn_2.atom_map[8], [7, 8])
+        expected_xyz = {'symbols': ('C', 'C', 'N', 'O', 'N', 'N', 'H', 'H', 'H'),
+                        'isotopes': (12, 12, 14, 16, 14, 14, 1, 1, 1),
+                        'coords': ((-1.0108, -0.0114, -0.061), (0.478, 0.0191, 0.0139), (1.2974, -0.993, 0.4693),
+                                   (0.6928, -1.9845, 0.8337), (1.7456, 1.9701, -0.6976), (1.1642, 1.0763, -0.3716),
+                                   (-1.4329, -0.1554, 0.9349), (-1.402, 0.9134, -0.4821), (-1.3327, -0.8499, -0.6803))}
+        self.assertEqual(mapped_product.get_xyz(), expected_xyz)
+
+    def test_check_attributes(self):
+        """Test checking the reaction attributes"""
+        rxn_1 = ARCReaction(label='H + [O-][N+](=N)N=O <=> [N-]=[N+](N=O)[O] + H2',
+                            r_species=[ARCSpecies(label='H', smiles='[H]'),
+                                       ARCSpecies(label='[O-][N+](=N)N=O', smiles='[O-][N+](=N)N=O')],
+                            p_species=[ARCSpecies(label='H2', smiles='[H][H]'),
+                                       ARCSpecies(label='[N-]=[N+](N=O)[O]', smiles='[N-]=[N+](N=O)[O]')],
+                            )
+        rxn_1.check_attributes()
+        self.assertEqual(rxn_1.reactants, ['H', '[O-][Np][=N]N=O'])
+        self.assertEqual(rxn_1.products, ['H2', '[N-]=[Np][N=O][O]'])
+        self.assertEqual(rxn_1.r_species[1].label, '[O-][Np][=N]N=O')
+
+    def test_remove_dup_species(self):
+        """Test the remove_dup_species function"""
+        species_list = [ARCSpecies(label='OH', smiles='[OH]'),
+                        ARCSpecies(label='OH', smiles='[OH]'),
+                        ARCSpecies(label='H', smiles='[H]'),
+                        ARCSpecies(label='H', smiles='[H]'),
+                        ARCSpecies(label='H2O', smiles='O'),
+                        ]
+        new_species_list = remove_dup_species(species_list=species_list)
+        self.assertEqual(len(new_species_list), 3)
+
+    def test_check_done_opt_r_n_p(self):
+        """Test the check_done_opt_r_n_p() method"""
+        c3_1_path = os.path.join(ARC_PATH, 'arc', 'testing', 'yml_testing', 'C3_1.yml')  # 1-propyl
+        c3_2_path = os.path.join(ARC_PATH, 'arc', 'testing', 'yml_testing', 'C3_2.yml')  # 2-propyl
+        c3_1_spc = ARCSpecies(yml_path=c3_1_path)
+        c3_2_spc = ARCSpecies(yml_path=c3_2_path)
+        rxn_1 = ARCReaction(r_species=[c3_1_spc], p_species=[c3_2_spc])
+        self.assertIsNone(rxn_1.done_opt_r_n_p)
+        rxn_1.check_done_opt_r_n_p()
+        self.assertEqual(rxn_1.done_opt_r_n_p, True)
+
+        rxn_2 = ARCReaction(r_species=[ARCSpecies(label='C1_3', smiles='[CH2]CC')],
+                            p_species=[ARCSpecies(label='C3_2', smiles='C[CH]C')])
+        rxn_2.check_done_opt_r_n_p()
+        self.assertEqual(rxn_2.done_opt_r_n_p, False)
+
+    def tests_white_space_in_reaction_label(self):
+        """Test that an extra white space in the reaction label does not confuse ARC."""
+        hno = ARCSpecies(label='HNO', smiles='N=O')
+        h2no = ARCSpecies(label='H2NO', smiles='N[O]')
+        no = ARCSpecies(label='NO', smiles='[N]=O')
+        nh2oh = ARCSpecies(label='NH2OH', smiles='NO')
+        rxn_1 = ARCReaction(label='HNO + H2NO <=> NO + NH2OH ',
+                            r_species=[hno, h2no], p_species=[no, nh2oh],
+                            )
+        self.assertEqual(rxn_1.reactants, ['H2NO', 'HNO'])
+        self.assertEqual(rxn_1.products, ['NH2OH', 'NO'])
+
+        rxn_2 = ARCReaction(reaction_dict={'label': 'HNO + H2NO <=> NO + NH2OH '},
+                            species_list=[hno, h2no, no, nh2oh],
+                            )
+        self.assertEqual(rxn_2.reactants, ['H2NO', 'HNO'])
+        self.assertEqual(rxn_2.products, ['NH2OH', 'NO'])
+
+    def tests_special_characters_in_reaction_label(self):
+        """Test that the respective species objects can be identified from a reaction label with a special character."""
+        no2 = ARCSpecies(label='NO2', smiles='[O]N=O')
+        nh3o = ARCSpecies(label='[O-][NH3+]', smiles='[O-][NH3+]')
+        hono = ARCSpecies(label='HONO', smiles='ON=O')
+        h2no = ARCSpecies(label='H2NO', smiles='N[O]')
+        rxn_1 = ARCReaction(label='NO2 + [O-][NH3+] <=> HONO + H2NO',
+                            r_species=[no2, nh3o], p_species=[hono, h2no],
+                            )
+        self.assertEqual(rxn_1.reactants, ['NO2', '[O-][NH3p]'])
+        self.assertEqual(rxn_1.products, ['H2NO', 'HONO'])
+
+        rxn_2 = ARCReaction(reaction_dict={'label': 'NO2 + [O-][NH3+] <=> HONO + H2NO'},
+                            species_list=[no2, nh3o, hono, h2no],
+                            )
+        self.assertEqual(rxn_2.reactants, ['NO2', '[O-][NH3p]'])
+        self.assertEqual(rxn_2.products, ['H2NO', 'HONO'])
+
+    def test_get_element_masses(self):
+        """Test the get_element_masses() method."""
+        self.assertTrue(almost_equal_lists(self.rxn1.get_element_mass(),
+                                           [12.0, 1.00782503224, 1.00782503224, 1.00782503224,
+                                            1.00782503224, 15.99491461957, 1.00782503224]))
+        self.assertTrue(almost_equal_lists(self.rxn2.get_element_mass(),
+                                           [12.0, 12.0, 1.00782503224, 1.00782503224, 1.00782503224, 1.00782503224,
+                                            1.00782503224, 15.99491461957, 1.00782503224]))
+        self.assertTrue(almost_equal_lists(self.rxn3.get_element_mass(),
+                                           [12.0, 12.0, 14.00307400443, 1.00782503224, 1.00782503224, 1.00782503224,
+                                            1.00782503224, 1.00782503224, 1.00782503224]))
+        self.assertTrue(almost_equal_lists(self.rxn5.get_element_mass(),
+                                           [14.00307400443, 1.00782503224, 1.00782503224,
+                                            14.00307400443, 1.00782503224, 1.00782503224]))
+
+    def test_get_bonds(self):
+        """Test the get_bonds() method."""
+        r_bonds, p_bonds = self.rxn1.get_bonds()
+        self.assertEqual(r_bonds, [(0, 1), (0, 2), (0, 3), (0, 4), (5, 6)])  # CH4 + OH
+        self.assertEqual(p_bonds, [(0, 1), (0, 2), (0, 3), (4, 5), (4, 6)])  # CH3 + H2O
+
+    def test_multi_reactants(self):
+        """Test that a reaction can be defined with many (>3) reactants or products given ts_xyz_guess."""
+        with self.assertRaises(ReactionError):
+            ARCReaction(r_species=[ARCSpecies(label='C2H6', smiles='CC'),
+                                   ARCSpecies(label='OH', smiles='[OH]'),
+                                   ARCSpecies(label='H2O', smiles='O'),
+                                   ARCSpecies(label='H2O', smiles='O')],
+                        p_species=[ARCSpecies(label='C2H5', smiles='C[CH2]'),
+                                   ARCSpecies(label='H2O', smiles='O'),
+                                   ARCSpecies(label='H2O', smiles='O'),
+                                   ARCSpecies(label='H2O', smiles='O')])
+
+        ARCReaction(r_species=[ARCSpecies(label='C2H6', smiles='CC'),
+                               ARCSpecies(label='OH', smiles='[OH]'),
+                               ARCSpecies(label='H2O', smiles='O'),
+                               ARCSpecies(label='H2O', smiles='O')],
+                    p_species=[ARCSpecies(label='C2H5', smiles='C[CH2]'),
+                               ARCSpecies(label='H2O', smiles='O'),
+                               ARCSpecies(label='H2O', smiles='O'),
+                               ARCSpecies(label='H2O', smiles='O')],
+                    ts_xyz_guess=["""C      -3.61598200   -0.14868700   -0.24629000
+                                    C      -2.87249000   -0.46501800   -1.37357200
+                                    H      -1.49356900   -0.33047800   -1.35181200
+                                    H      -0.84385200    0.11582900   -0.20370300
+                                    H      -1.59912100    0.44823500    0.91958000
+                                    H      -2.97672300    0.31399300    0.89602200
+                                    H      -4.69390100   -0.24965500   -0.26210800
+                                    H      -3.36776700   -0.80869200   -2.27293600
+                                    O      -0.91216500   -0.55783000   -2.23774700
+                                    H      -1.09587000    0.85059200    1.79098900
+                                    O      -3.55685000    0.58245300    1.76982000
+                                    H       0.61957500    0.23804900   -0.17583200
+                                    H       1.21746400   -1.55405900    0.34558600
+                                    O       2.65817800   -1.34488900    0.51012400
+                                    H       3.16323600   -2.29177100    0.72530400
+                                    H       3.06938800   -0.89699200   -0.39503300"""])
+
+    def test_load_ts_xyz_user_guess_from_files(self):
+        """Test various loading a reaction and populating the TS ARCSpecies with user xyz guesses from files"""
+        project_directory = os.path.join(ARC_PATH, 'arc', 'testing', 'reactions', 'methanoate_hydrolysis')
+        input_dict = read_yaml_file(path=os.path.join(project_directory, 'input_1.yml'))
+        input_dict['project_directory'] = project_directory
+        arc_object = ARC(**input_dict)
+        Scheduler(project=arc_object.project,
+                  species_list=arc_object.species,
+                  rxn_list=arc_object.reactions,
+                  conformer_level=arc_object.conformer_level,
+                  opt_level=arc_object.opt_level,
+                  freq_level=arc_object.freq_level,
+                  sp_level=arc_object.sp_level,
+                  scan_level=arc_object.scan_level,
+                  ts_guess_level=arc_object.ts_guess_level,
+                  ess_settings=arc_object.ess_settings,
+                  job_types=arc_object.job_types,
+                  rmg_database=arc_object.rmg_database,
+                  project_directory=arc_object.project_directory,
+                  ts_adapters=arc_object.ts_adapters,
+                  testing=True,
+                  )
+        self.assertEqual(len(arc_object.reactions[0].ts_species.ts_guesses[0].initial_xyz['symbols']), 19)
+        self.assertEqual(len(arc_object.reactions[0].ts_species.ts_guesses[1].initial_xyz['symbols']), 19)
+
+        input_dict = read_yaml_file(path=os.path.join(project_directory, 'input_2.yml'))
+        input_dict['project_directory'] = project_directory
+        arc_object = ARC(**input_dict)
+        Scheduler(project=arc_object.project,
+                  species_list=arc_object.species,
+                  rxn_list=arc_object.reactions,
+                  conformer_level=arc_object.conformer_level,
+                  opt_level=arc_object.opt_level,
+                  freq_level=arc_object.freq_level,
+                  sp_level=arc_object.sp_level,
+                  scan_level=arc_object.scan_level,
+                  ts_guess_level=arc_object.ts_guess_level,
+                  ess_settings=arc_object.ess_settings,
+                  job_types=arc_object.job_types,
+                  rmg_database=arc_object.rmg_database,
+                  project_directory=arc_object.project_directory,
+                  ts_adapters=arc_object.ts_adapters,
+                  testing=True,
+                  )
+        self.assertEqual(len(arc_object.reactions[0].ts_species.ts_guesses), 2)
+        self.assertEqual(len(arc_object.reactions[0].ts_species.ts_guesses[1].initial_xyz['symbols']), 19)
+
+    def test_get_rxn_smiles(self):
+        """Tests the get_rxn_smiles method"""
+        self.assertEqual(self.rxn1.get_rxn_smiles(), "C.[OH]>>[CH3].O")
+        self.assertEqual(self.rxn2.get_rxn_smiles(), "C[CH2].[OH]>>C=C.O")
+        self.assertEqual(self.rxn3.get_rxn_smiles(), "CC[NH]>>[CH2]CN")
+        self.assertEqual(self.rxn4.get_rxn_smiles(), "[NH2].[NH]N>>N.[N]N")
+        self.assertEqual(self.rxn5.get_rxn_smiles(), "[NH2].[NH2]>>[NH].N")
+        self.assertEqual(self.rxn6.get_rxn_smiles(), "[NH2].[NH]N>>N.[N-]=[NH2+]")
+        self.assertEqual(self.rxn7.get_rxn_smiles(), "[NH2].[NH]N>>N.[N]N")
+        self.assertEqual(self.rxn8.get_rxn_smiles(), "C.[OH]>>[CH3].O")
+        self.assertEqual(self.rxn9.get_rxn_smiles(), "NCO[O]>>C=N.[O]O")
+        self.assertEqual(self.rxn10.get_rxn_smiles(), "N=O.[O-][N+]=O>>[O-][NH+]=O.[N]=O")
+        self.assertEqual(self.rxn11.get_rxn_smiles(), "C[CH]C>>[CH2]CC")
+
+    @classmethod
+    def tearDownClass(cls):
+        """A function that is run ONCE after all unit tests in this class."""
+        project_directory = os.path.join(ARC_PATH, 'arc', 'testing', 'reactions', 'methanoate_hydrolysis')
+        sub_folders = ['log_and_restart_archive', 'output']
+        files_to_remove = ['arc.log']
+        for sub_folder in sub_folders:
+            shutil.rmtree(os.path.join(project_directory, sub_folder), ignore_errors=True)
+        for file_path in files_to_remove:
+            full_file_path = os.path.join(project_directory, file_path)
+            if os.path.isfile(full_file_path):
+                os.remove(full_file_path)
+
+
+if __name__ == '__main__':
+    unittest.main(testRunner=unittest.TextTestRunner(verbosity=2))
diff --git a/arc/reaction/reaction_test.py~hydrolysis b/arc/reaction/reaction_test.py~hydrolysis
new file mode 100644
index 0000000000..7dd088715b
--- /dev/null
+++ b/arc/reaction/reaction_test.py~hydrolysis
@@ -0,0 +1,1939 @@
+#!/usr/bin/env python3
+# encoding: utf-8
+
+"""
+This module contains unit tests of the arc.reaction.reaction module
+"""
+
+from itertools import permutations
+import os
+import shutil
+import unittest
+
+from rmgpy.reaction import Reaction
+from rmgpy.species import Species
+
+from arc.common import ARC_PATH, almost_equal_lists, read_yaml_file
+from arc.exceptions import ReactionError
+from arc.main import ARC
+from arc.reaction.reaction import ARCReaction, remove_dup_species
+from arc.scheduler import Scheduler
+from arc.species import ARCSpecies
+from arc.mapping.engine import check_atom_map, label_species_atoms
+
+
+class TestARCReaction(unittest.TestCase):
+    """
+    Contains unit tests for the ARCSpecies class
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """
+        A method that is run before all unit tests in this class.
+        """
+        cls.maxDiff = None
+
+        cls.h2_xyz = {'coords': ((0, 0, 0.3736550), (0, 0, -0.3736550)), 'isotopes': (1, 1), 'symbols': ('H', 'H')}
+        cls.o2_xyz = {'coords': ((0, 0, 0.6487420), (0, 0, -0.6487420)), 'isotopes': (16, 16), 'symbols': ('O', 'O')}
+        cls.co_xyz = {'coords': ((0, 0, -0.6748240), (0, 0, 0.5061180)), 'isotopes': (12, 16), 'symbols': ('C', 'O')}
+        cls.ho2_xyz = {'coords': ((0.0558910, -0.6204870, 0.0000000),
+                                  (0.0558910, 0.7272050, 0.0000000),
+                                  (-0.8942590, -0.8537420, 0.0000000)),
+                       'isotopes': (16, 16, 1), 'symbols': ('O', 'O', 'H')}
+        cls.ch2_xyz = {'coords': ((-1.3519460059345912e-10, -5.04203763365717e-10, 0.0),
+                                  (-1.064874800478917, -0.016329711355091817, 0.0),
+                                  (1.0648748006141107, 0.016329711859301474, 0.0)),
+                       'isotopes': (12, 1, 1), 'symbols': ('C', 'H', 'H')}
+        cls.nh_xyz = {'coords': ((0.509499983131626, 0.0, 0.0), (-0.509499983131626, 0.0, 0.0)),
+                      'isotopes': (14, 1), 'symbols': ('N', 'H')}
+        cls.ch2choh_xyz = """C      -0.80601307   -0.11773769    0.32792128
+                             C       0.23096883    0.47536513   -0.26437348
+                             O       1.44620485   -0.11266560   -0.46339257
+                             H      -1.74308628    0.41660480    0.45016601
+                             H      -0.75733964   -1.13345488    0.70278513
+                             H       0.21145717    1.48838416   -0.64841675
+                             H       1.41780836   -1.01649567   -0.10468897"""
+        cls.ch3cho_xyz = """C      -0.64851652   -0.03628781   -0.04007233
+                            C       0.84413281    0.04088405    0.05352862
+                            O       1.47323666   -0.23917853    1.06850992
+                            H      -1.06033881    0.94648764   -0.28238370
+                            H      -0.92134271   -0.74783968   -0.82281679
+                            H      -1.04996634   -0.37234114    0.91874740
+                            H       1.36260637    0.37153887   -0.86221771"""
+        cls.ch4_xyz = """C      -0.00000000    0.00000000    0.00000000
+                         H      -0.65055201   -0.77428020   -0.41251879
+                         H      -0.34927558    0.98159583   -0.32768232
+                         H      -0.02233792   -0.04887375    1.09087665
+                         H       1.02216551   -0.15844188   -0.35067554"""
+        cls.oh_xyz = """O       0.48890387    0.00000000    0.00000000
+                        H      -0.48890387    0.00000000    0.00000000"""
+        cls.ch3_xyz = """C       0.00000000    0.00000001   -0.00000000
+                         H       1.06690511   -0.17519582    0.05416493
+                         H      -0.68531716   -0.83753536   -0.02808565
+                         H      -0.38158795    1.01273118   -0.02607927"""
+        cls.h2o_xyz = """O      -0.00032832    0.39781490    0.00000000
+                         H      -0.76330345   -0.19953755    0.00000000
+                         H       0.76363177   -0.19827735    0.00000000"""
+        cls.ch3chch3_xyz = """C                  0.50180491   -0.93942231   -0.57086745
+                              C                  0.01278145    0.13148427    0.42191407
+                              C                 -0.86874485    1.29377369   -0.07163907
+                              H                  0.28549447    0.06799101    1.45462711
+                              H                  1.44553946   -1.32386345   -0.24456986
+                              H                  0.61096295   -0.50262210   -1.54153222
+                              H                 -0.24653265    2.11136864   -0.37045418
+                              H                 -0.21131163   -1.73585284   -0.61629002
+                              H                 -1.51770930    1.60958621    0.71830245
+                              H                 -1.45448167    0.96793094   -0.90568876"""
+        cls.ch3ch2ch2_xyz = """C                  0.48818717   -0.94549701   -0.55196729
+                               C                  0.35993708    0.29146456    0.35637075
+                               C                 -0.91834764    1.06777042   -0.01096751
+                               H                  0.30640232   -0.02058840    1.37845537
+                               H                  1.37634603   -1.48487836   -0.29673876
+                               H                  0.54172192   -0.63344406   -1.57405191
+                               H                  1.21252186    0.92358349    0.22063264
+                               H                 -0.36439762   -1.57761595   -0.41622918
+                               H                 -1.43807526    1.62776079    0.73816131
+                               H                 -1.28677889    1.04716138   -1.01532486"""
+        cls.rxn1 = ARCReaction(r_species=[ARCSpecies(label='CH4', smiles='C'), ARCSpecies(label='OH', smiles='[OH]')],
+                               p_species=[ARCSpecies(label='CH3', smiles='[CH3]'), ARCSpecies(label='H2O', smiles='O')])
+        cls.rxn2 = ARCReaction(r_species=[ARCSpecies(label='C2H5', smiles='C[CH2]'), ARCSpecies(label='OH', smiles='[OH]')],
+                               p_species=[ARCSpecies(label='C=C', smiles='C2H4'), ARCSpecies(label='H2O', smiles='O')])
+        cls.rxn3 = ARCReaction(r_species=[ARCSpecies(label='CC[NH]', smiles='CH3CH2NH')],
+                               p_species=[ARCSpecies(label='[CH2]CH', smiles='CH2CH2NH2')])
+        cls.rxn4 = ARCReaction(r_species=[ARCSpecies(label='NH2', smiles='[NH2]'), ARCSpecies(label='N[NH]', smiles='NH2NH')],
+                               p_species=[ARCSpecies(label='NH3', smiles='N'), ARCSpecies(label='N[N]', smiles='NH2N')])
+        cls.rxn5 = ARCReaction(reactants=['NH2', 'NH2'], products=['NH', 'NH3'],
+                               r_species=[ARCSpecies(label='NH2', smiles='[NH2]')],
+                               p_species=[ARCSpecies(label='NH', smiles='[NH]'),
+                                          ARCSpecies(label='NH3', smiles='N')])
+        cls.rxn6 = ARCReaction(reactants=['NH2', 'N2H3'], products=['NH3', 'H2NN(S)'],
+                               r_species=[ARCSpecies(label='NH2', smiles='[NH2]'),
+                                          ARCSpecies(label='N2H3', smiles='N[NH]')],
+                               p_species=[ARCSpecies(label='NH3', smiles='N'),
+                                          ARCSpecies(label='H2NN(S)', adjlist="""multiplicity 1
+                                                                                 1 N u0 p0 c+1 {2,D} {3,S} {4,S}
+                                                                                 2 N u0 p2 c-1 {1,D}
+                                                                                 3 H u0 p0 c0 {1,S}
+                                                                                 4 H u0 p0 c0 {1,S}""")])
+        cls.rxn7 = ARCReaction(reactants=['NH2', 'N2H3'], products=['NH3', 'H2NN(T)'],
+                               r_species=[ARCSpecies(label='NH2', smiles='[NH2]'),
+                                          ARCSpecies(label='N2H3', smiles='N[NH]')],
+                               p_species=[ARCSpecies(label='NH3', smiles='N'),
+                                          ARCSpecies(label='H2NN(T)', adjlist="""multiplicity 3
+                                                                                 1 N u0 p1 c0 {2,S} {3,S} {4,S}
+                                                                                 2 N u2 p1 c0 {1,S}
+                                                                                 3 H u0 p0 c0 {1,S}
+                                                                                 4 H u0 p0 c0 {1,S}""")])
+        cls.rxn8 = ARCReaction(r_species=[ARCSpecies(label='CH4', smiles='C', xyz=cls.ch4_xyz),
+                                          ARCSpecies(label='OH', smiles='[OH]', xyz=cls.oh_xyz)],
+                               p_species=[ARCSpecies(label='CH3', smiles='[CH3]', xyz=cls.ch3_xyz),
+                                          ARCSpecies(label='H2O', smiles='O', xyz=cls.h2o_xyz)])
+        cls.rxn9 = ARCReaction(r_species=[ARCSpecies(label='NCOO', smiles='NCO[O]')],
+                               p_species=[ARCSpecies(label='NHCH2', smiles='N=C'),
+                                          ARCSpecies(label='HO2', smiles='O[O]')])
+        cls.rxn10 = ARCReaction(r_species=[ARCSpecies(label='HNO', smiles='N=O'),
+                                           ARCSpecies(label='NO2', smiles='O=[N+][O-]')],
+                                p_species=[ARCSpecies(label='HNO2', smiles='[O-][NH+]=O'),
+                                           ARCSpecies(label='NO', smiles='[N]=O')])
+        cls.rxn11 = ARCReaction(r_species=[ARCSpecies(label='C[CH]C', smiles='C[CH]C', xyz=cls.ch3chch3_xyz)],
+                                p_species=[ARCSpecies(label='[CH2]CC', smiles='[CH2]CC', xyz=cls.ch3ch2ch2_xyz)])
+
+    def test_str(self):
+        """Test the string representation of the object"""
+        str_representation = str(self.rxn1)
+        self.assertEqual(self.rxn1.charge, 0)
+        expected_representation = 'ARCReaction(label="CH4 + OH <=> CH3 + H2O", ' \
+                                  'rmg_reaction="CH4 + OH <=> CH3 + H2O", ' \
+                                  'multiplicity=2, charge=0)'
+        self.assertEqual(str_representation, expected_representation)
+
+    def test_as_dict(self):
+        """Test ARCReaction.as_dict()"""
+        rxn_dict_1 = self.rxn1.as_dict()
+        # mol.atoms are not tested since all id's (including connectivity) changes depending on how the test is run.
+        expected_dict_1 = {'family': 'H_Abstraction',
+                           'family_own_reverse': True,
+                           'label': 'CH4 + OH <=> CH3 + H2O',
+                           'multiplicity': 2,
+                           'p_species': [{'bond_corrections': {'C-H': 3},
+                                          'cheap_conformer': 'C       0.00000000    0.00000001   -0.00000000\n'
+                                                             'H       1.06690511   -0.17519582    0.05416493\n'
+                                                             'H      -0.68531716   -0.83753536   -0.02808565\n'
+                                                             'H      -0.38158795    1.01273118   -0.02607927',
+                                          'label': 'CH3',
+                                          'long_thermo_description': "Bond corrections: {'C-H': 3}\n",
+                                          'mol': {'atom_order': rxn_dict_1['p_species'][0]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_1['p_species'][0]['mol']['atoms'],
+                                                  'multiplicity': 2,
+                                                  'props': {}},
+                                          'multiplicity': 2,
+                                          'number_of_rotors': 0},
+                                         {'bond_corrections': {'H-O': 2},
+                                          'cheap_conformer': 'O      -0.00032832    0.39781490    0.00000000\n'
+                                                             'H      -0.76330345   -0.19953755    0.00000000\n'
+                                                             'H       0.76363177   -0.19827735    0.00000000',
+                                          'label': 'H2O',
+                                          'long_thermo_description': "Bond corrections: {'H-O': 2}\n",
+                                          'mol': {'atom_order': rxn_dict_1['p_species'][1]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_1['p_species'][1]['mol']['atoms'],
+                                                  'multiplicity': 1,
+                                                  'props': {}},
+                                          'multiplicity': 1,
+                                          'number_of_rotors': 0}],
+                           'products': ['CH3', 'H2O'],
+                           'r_species': [{'bond_corrections': {'C-H': 4},
+                                          'cheap_conformer': 'C      -0.00000000   -0.00000000    0.00000000\n'
+                                                             'H      -0.63306457   -0.78034118   -0.42801448\n'
+                                                             'H      -0.38919244    0.98049560   -0.28294367\n'
+                                                             'H       0.00329661   -0.09013273    1.08846898\n'
+                                                             'H       1.01896040   -0.11002169   -0.37751083',
+                                          'label': 'CH4',
+                                          'long_thermo_description': "Bond corrections: {'C-H': 4}\n",
+                                          'mol': {'atom_order': rxn_dict_1['r_species'][0]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_1['r_species'][0]['mol']['atoms'],
+                                                  'multiplicity': 1,
+                                                  'props': {}},
+                                          'multiplicity': 1,
+                                          'number_of_rotors': 0},
+                                         {'bond_corrections': {'H-O': 1},
+                                          'cheap_conformer': 'O       0.00000000    0.00000000    0.61310000\n'
+                                                             'H       0.00000000    0.00000000   -0.61310000',
+                                          'label': 'OH',
+                                          'long_thermo_description': "Bond corrections: {'H-O': 1}\n",
+                                          'mol': {'atom_order': rxn_dict_1['r_species'][1]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_1['r_species'][1]['mol']['atoms'],
+                                                  'multiplicity': 2,
+                                                  'props': {}},
+                                          'multiplicity': 2,
+                                          'number_of_rotors': 0}],
+                           'reactants': ['CH4', 'OH'],
+                           }
+        self.assertEqual(rxn_dict_1, expected_dict_1)
+
+        rxn_dict_6 = self.rxn6.as_dict()
+        # The ``long_thermo_description`` attribute isn't deterministic (order could change)
+        expected_dict_6 = {'label': 'NH2 + N2H3 <=> NH3 + H2NN[S]',
+                           'family': 'Disproportionation',
+                           'multiplicity': 1,
+                           'p_species': [{'bond_corrections': {'H-N': 3},
+                                          'cheap_conformer': 'N       0.00064924   -0.00099698    0.29559292\n'
+                                                             'H      -0.41786606    0.84210396   -0.09477452\n'
+                                                             'H      -0.52039228   -0.78225292   -0.10002797\n'
+                                                             'H       0.93760911   -0.05885406   -0.10079043',
+                                          'label': 'NH3',
+                                          'long_thermo_description': "Bond corrections: {'H-N': 3}\n",
+                                          'mol': {'atom_order': rxn_dict_6['p_species'][0]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_6['p_species'][0]['mol']['atoms'],
+                                                  'multiplicity': 1,
+                                                  'props': {}},
+                                          'multiplicity': 1,
+                                          'number_of_rotors': 0},
+                                         {'adjlist': """multiplicity 1
+1 N u0 p0 c+1 {2,D} {3,S} {4,S}
+2 N u0 p2 c-1 {1,D}
+3 H u0 p0 c0 {1,S}
+4 H u0 p0 c0 {1,S}""",
+                                          'bond_corrections': {'H-N': 2, 'N=N': 1},
+                                          'cheap_conformer': 'N      -0.08201544    0.01567102    0.28740725\n'
+                                                             'N       1.12656450   -0.21525765   -0.48621674\n'
+                                                             'H      -0.50742562   -0.72901556    0.83982059\n'
+                                                             'H      -0.53712345    0.92860218    0.29862267',
+                                          'label': 'H2NN[S]',
+                                          'long_thermo_description': rxn_dict_6['p_species'][1]['long_thermo_description'],
+                                          'mol': {'atom_order': rxn_dict_6['p_species'][1]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_6['p_species'][1]['mol']['atoms'],
+                                                  'multiplicity': 1,
+                                                  'props': {}},
+                                          'multiplicity': 1,
+                                          'number_of_rotors': 0,
+                                          'original_label': 'H2NN(S)'}],
+                           'products': ['H2NN[S]', 'NH3'],
+                           'r_species': [{'bond_corrections': {'H-N': 2},
+                                          'cheap_conformer': 'N       0.00016375    0.40059499    0.00000000\n'
+                                                             'H      -0.83170922   -0.19995756    0.00000000\n'
+                                                             'H       0.83154548   -0.20063742    0.00000000',
+                                          'label': 'NH2',
+                                          'long_thermo_description': "Bond corrections: {'H-N': 2}\n",
+                                          'mol': {'atom_order': rxn_dict_6['r_species'][0]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_6['r_species'][0]['mol']['atoms'],
+                                                  'multiplicity': 2,
+                                                  'props': {}},
+                                          'multiplicity': 2,
+                                          'number_of_rotors': 0},
+                                         {'bond_corrections': {'H-N': 3, 'N-N': 1},
+                                          'cheap_conformer': 'N      -0.46751749    0.03795671    0.31180026\n'
+                                                             'N       0.79325823   -0.46038094   -0.24114357\n'
+                                                             'H      -1.19307188   -0.63034971    0.05027053\n'
+                                                             'H      -0.69753009    0.90231202   -0.17907452\n'
+                                                             'H       1.56486123    0.15046192    0.05814730',
+                                          'label': 'N2H3',
+                                          'long_thermo_description': rxn_dict_6['r_species'][1]['long_thermo_description'],
+                                          'mol': {'atom_order': rxn_dict_6['r_species'][1]['mol']['atom_order'],
+                                                  'atoms': rxn_dict_6['r_species'][1]['mol']['atoms'],
+                                                  'multiplicity': 2,
+                                                  'props': {}},
+                                          'multiplicity': 2,
+                                          'number_of_rotors': 0}],
+                           'reactants': ['N2H3', 'NH2'],
+                           }
+        self.assertEqual(rxn_dict_6, expected_dict_6)
+
+    def test_from_dict(self):
+        """Test ARCReaction.from_dict()"""
+        rxn_dict = self.rxn1.as_dict()
+        rxn = ARCReaction(reaction_dict=rxn_dict)
+        self.assertEqual(rxn.label, 'CH4 + OH <=> CH3 + H2O')
+        self.assertEqual(rxn.multiplicity, 2)
+        self.assertEqual(rxn.charge, 0)
+        self.assertEqual(rxn.family, 'H_Abstraction')
+        self.assertEqual(rxn.family_own_reverse, True)
+        self.assertEqual(rxn.reactants, ['CH4', 'OH'])
+        self.assertEqual(rxn.products, ['CH3', 'H2O'])
+        self.assertIsNone(rxn.index)
+
+    def test_copy(self):
+        """Test the copy() method."""
+        rxn_copy = self.rxn1.copy()
+        self.assertIsNot(self.rxn1, rxn_copy)
+        self.assertEqual(rxn_copy.multiplicity, self.rxn1.multiplicity)
+        self.assertEqual(rxn_copy.label, self.rxn1.label)
+
+        rxn_copy = self.rxn8.copy()
+        self.assertIsNot(self.rxn8, rxn_copy)
+        self.assertEqual(self.rxn8.label, rxn_copy.label)
+        self.assertEqual(self.rxn8.multiplicity, rxn_copy.multiplicity)
+        self.assertEqual(self.rxn8.charge, rxn_copy.charge)
+        self.assertTrue(check_atom_map(self.rxn8))
+        self.assertTrue(check_atom_map(rxn_copy))
+        self.assertEqual(self.rxn8.atom_map, rxn_copy.atom_map)
+        self.assertEqual(tuple(spc.label for spc in self.rxn8.r_species),
+                         tuple(spc.label for spc in rxn_copy.r_species))
+        self.assertEqual(tuple(spc.label for spc in self.rxn8.p_species),
+                         tuple(spc.label for spc in rxn_copy.p_species))
+        self.assertNotIn(self.rxn8.r_species[0].mol.atoms[0].id, [atom.id for atom in rxn_copy.r_species[0].mol.atoms
+                                                                  + rxn_copy.p_species[0].mol.atoms])
+
+    def test_flip_reaction(self):
+        """Test the flip_reaction() method."""
+        flipped_rxn = self.rxn1.flip_reaction()
+        self.assertIsNot(self.rxn1, flipped_rxn)
+        self.assertEqual(flipped_rxn.multiplicity, self.rxn1.multiplicity)
+        self.assertNotEqual(flipped_rxn.label, self.rxn1.label)
+        for s1, s2 in zip(self.rxn1.r_species, flipped_rxn.p_species):
+            self.assertEqual(s1.label, s2.label)
+            self.assertTrue(s1.mol.is_isomorphic(s2.mol))
+        for s1, s2 in zip(self.rxn1.p_species, flipped_rxn.r_species):
+            self.assertEqual(s1.label, s2.label)
+            self.assertTrue(s1.mol.is_isomorphic(s2.mol))
+
+        flipped_rxn = self.rxn8.flip_reaction()
+        self.assertIsNot(self.rxn8, flipped_rxn)
+        self.assertNotEqual(self.rxn8.label, flipped_rxn.label)
+        self.assertEqual(self.rxn8.label.split('<=>')[0].strip(), flipped_rxn.label.split('<=>')[1].strip())
+        self.assertEqual(self.rxn8.label.split('<=>')[1].strip(), flipped_rxn.label.split('<=>')[0].strip())
+        self.assertEqual(self.rxn8.multiplicity, flipped_rxn.multiplicity)
+        self.assertEqual(self.rxn8.charge, flipped_rxn.charge)
+        self.assertTrue(check_atom_map(flipped_rxn))
+        self.assertEqual(self.rxn8.atom_map[0], 0)
+        self.assertEqual(self.rxn8.atom_map[5], 4)
+        self.assertEqual(flipped_rxn.atom_map[0], 0)
+        self.assertEqual(flipped_rxn.atom_map[4], 5)
+        self.assertEqual(tuple(spc.label for spc in self.rxn8.r_species),
+                         tuple(spc.label for spc in flipped_rxn.p_species))
+        self.assertEqual(tuple(spc.label for spc in self.rxn8.p_species),
+                         tuple(spc.label for spc in flipped_rxn.r_species))
+        self.assertNotIn(self.rxn8.r_species[0].mol.atoms[0].id, [atom.id for atom in flipped_rxn.r_species[0].mol.atoms
+                                                                  + flipped_rxn.p_species[0].mol.atoms])
+
+    def test_is_isomerization(self):
+        """Test the is_isomerization() method"""
+        self.assertFalse(self.rxn1.is_isomerization())
+        self.assertFalse(self.rxn2.is_isomerization())
+        self.assertTrue(self.rxn3.is_isomerization())
+        self.assertFalse(self.rxn4.is_isomerization())
+        self.assertFalse(self.rxn5.is_isomerization())
+        self.assertFalse(self.rxn6.is_isomerization())
+        self.assertFalse(self.rxn7.is_isomerization())
+        self.assertFalse(self.rxn8.is_isomerization())
+        self.assertFalse(self.rxn9.is_isomerization())
+
+    def test_rxn_family(self):
+        """Test that ARC gets the correct RMG family for different reactions"""
+        self.assertEqual(self.rxn1.family, 'H_Abstraction')
+        self.assertTrue(self.rxn1.family_own_reverse)
+        self.assertEqual(self.rxn2.family, 'Disproportionation')
+        self.assertFalse(self.rxn2.family_own_reverse)
+        self.assertEqual(self.rxn3.family, 'intra_H_migration')
+        self.assertTrue(self.rxn3.family_own_reverse)
+        self.assertEqual(self.rxn4.family, 'H_Abstraction')
+        self.rxn5.rmg_reaction_from_arc_species()
+        self.rxn5.check_attributes()
+        self.assertEqual(self.rxn5.family, 'H_Abstraction')
+        self.rxn9.rmg_reaction_from_arc_species()
+        self.rxn9.check_attributes()
+        self.assertEqual(self.rxn9.family, 'HO2_Elimination_from_PeroxyRadical')
+        rxn_9_flipped = self.rxn9.flip_reaction()
+        rxn_9_flipped.rmg_reaction_from_arc_species()
+        rxn_9_flipped.check_attributes()
+        self.assertEqual(rxn_9_flipped.family, 'HO2_Elimination_from_PeroxyRadical')
+        self.assertEqual(self.rxn10.family, 'H_Abstraction')
+        rxn_1 = ARCReaction(r_species=[ARCSpecies(label='C2H6', smiles='CC'),
+                                       ARCSpecies(label='CCOOj', smiles='CCO[O]')],
+                            p_species=[ARCSpecies(label='CCOOH', smiles='CCOO'),
+                                       ARCSpecies(label='C2H5', smiles='C[CH2]')])
+        rxn_1.check_attributes()
+        self.assertEqual(rxn_1.family, 'H_Abstraction')
+
+        # Test identifying the reaction family for with zwitterions read from Arkane YAML files
+        base_path = os.path.join(ARC_PATH, 'arc', 'testing', 'yml_testing', 'HNNO+NH3O=H2NO+NH2NO')
+        rxn2 = ARCReaction(r_species=[ARCSpecies(label='HNNO', smiles='[O-][N+]=N', yml_path=os.path.join(base_path, 'HNNO.yml')),
+                                      ARCSpecies(label='NH3O', smiles='[O-][NH3+]', yml_path=os.path.join(base_path, 'NH3O.yml'))],
+                           p_species=[ARCSpecies(label='H2NO', smiles='N[O]', yml_path=os.path.join(base_path, 'H2NO.yml')),
+                                      ARCSpecies(label='NH2NO', smiles='NN=O', yml_path=os.path.join(base_path, 'NH2NO.yml'))])
+        self.assertEqual(rxn2.family, 'H_Abstraction')
+
+    def test_charge_property(self):
+        """Test determining charge"""
+        self.assertEqual(self.rxn1.charge, 0)
+
+    def test_multiplicity_property(self):
+        """Test determining multiplicity"""
+        self.assertEqual(self.rxn1.multiplicity, 2)
+        self.assertEqual(self.rxn2.multiplicity, 1)
+        self.assertEqual(self.rxn3.multiplicity, 2)
+        self.assertEqual(self.rxn4.multiplicity, 3)
+        self.assertEqual(self.rxn5.multiplicity, 3)
+        self.assertEqual(self.rxn6.multiplicity, 1)
+        self.assertEqual(self.rxn7.multiplicity, 3)
+
+        # isomerization
+        rxn_1 = ARCReaction(reactants=['nC3H7'], products=['iC3H7'],
+                            r_species=[ARCSpecies(label='nC3H7', smiles='[CH2]CC')],
+                            p_species=[ARCSpecies(label='iC3H7', smiles='C[CH]C')])
+        self.assertEqual(rxn_1.multiplicity, 2)
+        rxn_2 = ARCReaction(reactants=['CC=O'], products=['C=COH'],
+                            r_species=[ARCSpecies(label='CC=O', smiles='CC=O')],
+                            p_species=[ARCSpecies(label='C=COH', smiles='C=CO')])
+        self.assertEqual(rxn_2.multiplicity, 1)
+
+        # unimolecular
+        rxn_3 = ARCReaction(reactants=['H', 'OH'], products=['H2O'],
+                            r_species=[ARCSpecies(label='H', smiles='[H]'), ARCSpecies(label='OH', smiles='[OH]')],
+                            p_species=[ARCSpecies(label='H2O', smiles='O')])
+        self.assertEqual(rxn_3.multiplicity, 1)
+
+        # Reactions for which the multiplicity was wrongly determined before code fixes:
+        rxn_4 = ARCReaction(reactants=['H', 'HO2'], products=['OH', 'OH'],
+                            r_species=[ARCSpecies(label='H', smiles='[H]'), ARCSpecies(label='HO2', smiles='O[O]')],
+                            p_species=[ARCSpecies(label='OH', smiles='[OH]'), ARCSpecies(label='OH', smiles='[OH]')])
+        self.assertEqual(rxn_4.multiplicity, 1)
+
+        rxn_5 = ARCReaction(r_species=[ARCSpecies(label='N', smiles='[N]'), ARCSpecies(label='HNO', smiles='N=O')],
+                            p_species=[ARCSpecies(label='NO', smiles='[N]=O'),
+                                       ARCSpecies(label='NH', smiles='[NH]')])
+        self.assertEqual(rxn_5.multiplicity, 4)
+        rxn_5 = ARCReaction(r_species=[ARCSpecies(label='N', smiles='[N]'), ARCSpecies(label='HNO', smiles='N=O')],
+                            p_species=[ARCSpecies(label='NO', smiles='[N]=O'), ARCSpecies(label='NH', smiles='[NH]')])
+        self.assertEqual(rxn_5.multiplicity, 4)
+
+    def test_check_atom_balance(self):
+        """Test the Reaction check_atom_balance method"""
+
+        # A normal reaction
+        rxn1 = ARCReaction(reactants=['CH4', 'OH'], products=['CH3', 'H2O'],
+                           r_species=[ARCSpecies(label='CH4', smiles='C'),
+                                      ARCSpecies(label='OH', smiles='[OH]')],
+                           p_species=[ARCSpecies(label='CH3', smiles='[CH3]'),
+                                      ARCSpecies(label='H2O', smiles='O')])
+        self.assertTrue(rxn1.check_atom_balance())
+
+        # A reaction with the same species twice on one side
+        rxn3 = ARCReaction(reactants=['CH4', 'OH', 'H2O'], products=['CH3', 'H2O', 'H2O'],
+                           r_species=[ARCSpecies(label='CH4', smiles='C'),
+                                      ARCSpecies(label='OH', smiles='[OH]'),
+                                      ARCSpecies(label='H2O', smiles='O')],
+                           p_species=[ARCSpecies(label='CH3', smiles='[CH3]'),
+                                      ARCSpecies(label='H2O', smiles='O')])
+        self.assertTrue(rxn3.check_atom_balance())
+
+        # Another reaction with the same species twice on one side
+        rxn4 = ARCReaction(reactants=['OH', 'OH'], products=['O', 'H2O'],
+                           r_species=[ARCSpecies(label='OH', smiles='[OH]')],
+                           p_species=[ARCSpecies(label='O', smiles='[O]'),
+                                      ARCSpecies(label='H2O', smiles='O')])
+        self.assertTrue(rxn4.check_atom_balance())
+
+        # Another reaction with the same species twice on one side, reading from the reaction label
+        nh2 = ARCSpecies(label='NH2', smiles='[NH2]')
+        h = ARCSpecies(label='H', smiles='[H]')
+        n2h3 = ARCSpecies(label='N2H3', smiles='[NH]N')
+        rxn_label = 'NH2 + NH2 <=> H + N2H3'
+        rxn5 = ARCReaction(reaction_dict={'label': rxn_label}, species_list=[nh2, h, n2h3])
+        self.assertTrue(rxn5.check_atom_balance())
+        rxn5_flipped = rxn5.flip_reaction()
+        self.assertTrue(rxn5_flipped.check_atom_balance())
+
+        # Legitimate reactions that previously failed in the atom balance test
+        rxn6 = ARCReaction(reactants=['NH', '[O-][N+](=N)N'], products=['NH2', '[N-]=[N+]([O])N'],
+                           r_species=[ARCSpecies(label='NH', smiles='[NH]'),
+                                      ARCSpecies(label='[O-][N+](=N)N', smiles='[O-][N+](=N)N')],
+                           p_species=[ARCSpecies(label='NH2', smiles='[NH2]'),
+                                      ARCSpecies(label='[N-]=[N+]([O])N', smiles='[N-]=[N+]([O])N')])
+        self.assertTrue(rxn6.check_atom_balance())
+
+        rxn7 = ARCReaction(reactants=['N3O2', 'HON'], products=['NO', 'HN3O2'],
+                           r_species=[ARCSpecies(label='N3O2', smiles='[N-]=[N+](N=O)[O]'),
+                                      ARCSpecies(label='HON', smiles='[OH+]=[N-]')],
+                           p_species=[ARCSpecies(label='NO', smiles='[N]=O'),
+                                      ARCSpecies(label='HN3O2', smiles='[O-][N+](=N)N=O')])
+        self.assertTrue(rxn7.check_atom_balance())
+
+        # A reaction that involves charged species
+        rxn8 = ARCReaction(reactants=['C6CNC3', 'OH'], products=['C6COH', 'NC3'],
+                           r_species=[ARCSpecies(label='C6CNC3', smiles='c1ccccc1C[N+](C)(C)C', charge=1, multiplicity=1),
+                                      ARCSpecies(label='OH', smiles='[OH-]', charge=-1, multiplicity=1)],
+                           p_species=[ARCSpecies(label='C6COH', smiles='c1ccccc1CO'),
+                                      ARCSpecies(label='NC3', smiles='CN(C)C')])
+        self.assertTrue(rxn8.check_atom_balance())
+
+        # A *non*-balanced reaction
+        with self.assertRaises(ReactionError):
+            ARCReaction(reactants=['CH4', 'OH'], products=['CH4', 'H2O'],
+                        r_species=[ARCSpecies(label='CH4', smiles='C'),
+                                   ARCSpecies(label='OH', smiles='[OH]')],
+                        p_species=[ARCSpecies(label='CH4', smiles='C'),
+                                   ARCSpecies(label='H2O', smiles='O')])
+
+    def test_get_species_count(self):
+        """Test the get_species_count() method"""
+        rxn1 = ARCReaction(reactants=['CH4', 'OH', 'H2O'], products=['CH3', 'H2O', 'H2O'])
+        spc1 = ARCSpecies(label='OH', smiles='[OH]')
+        spc2 = ARCSpecies(label='H2O', smiles='O')
+        # check by species
+        self.assertEqual(rxn1.get_species_count(species=spc1, well=0), 1)
+        self.assertEqual(rxn1.get_species_count(species=spc1, well=1), 0)
+        self.assertEqual(rxn1.get_species_count(species=spc2, well=0), 1)
+        self.assertEqual(rxn1.get_species_count(species=spc2, well=1), 2)
+        # check by label
+        self.assertEqual(rxn1.get_species_count(label=spc1.label, well=0), 1)
+        self.assertEqual(rxn1.get_species_count(label=spc1.label, well=1), 0)
+        self.assertEqual(rxn1.get_species_count(label=spc2.label, well=0), 1)
+        self.assertEqual(rxn1.get_species_count(label=spc2.label, well=1), 2)
+
+        h2nn = ARCSpecies(label='H2NN(T)', smiles='[N]N')
+        n2h2 = ARCSpecies(label='N2H4', smiles='NN')
+        n2h3 = ARCSpecies(label='N2H3', smiles='[NH]N')
+        rxn2 = ARCReaction(r_species=[h2nn, n2h2], p_species=[n2h3, n2h3])
+        self.assertEqual(rxn2.get_species_count(label=n2h3.label, well=1), 2)
+
+    def test_get_reactants_and_products(self):
+        """Test getting reactants and products"""
+        self.rxn1.remove_dup_species()
+        reactants, products = self.rxn1.get_reactants_and_products(arc=True)
+        for spc in reactants + products:
+            self.assertIsInstance(spc, ARCSpecies)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+
+        reactants, products = self.rxn1.get_reactants_and_products(arc=False)
+        for spc in reactants + products:
+            self.assertIsInstance(spc, Species)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+
+        reactants, products = self.rxn5.get_reactants_and_products(arc=True)
+        for spc in reactants + products:
+            self.assertIsInstance(spc, ARCSpecies)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+        self.assertEqual(reactants[0].label, reactants[1].label)
+
+        reactants, products = self.rxn5.get_reactants_and_products(arc=False)
+        for spc in reactants + products:
+            self.assertIsInstance(spc, Species)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+        self.assertNotEqual(products[0].label, products[1].label)
+
+        h2nn = ARCSpecies(label='H2NN(T)', smiles='[N]N')
+        n2h2 = ARCSpecies(label='N2H4', smiles='NN')
+        n2h3 = ARCSpecies(label='N2H3', smiles='[NH]N')
+        rxn1 = ARCReaction(r_species=[h2nn, n2h2], p_species=[n2h3, n2h3])
+        reactants, products = rxn1.get_reactants_and_products(arc=True, return_copies=False)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+        self.assertIs(products[0], products[1])
+        reactants, products = rxn1.get_reactants_and_products(arc=True, return_copies=True)
+        self.assertEqual(len(reactants), 2)
+        self.assertEqual(len(products), 2)
+        self.assertIsNot(products[0], products[1])
+
+    def test_get_expected_changing_bonds(self):
+        """Test the get_expected_changing_bonds() method."""
+        expected_breaking_bonds, expected_forming_bonds = self.rxn11.get_expected_changing_bonds(
+            r_label_dict={'*1': 1, '*2': 2, '*3': 6})
+        self.assertEqual(expected_breaking_bonds, [(2, 6)])
+        self.assertEqual(expected_forming_bonds, [(1, 6)])
+
+    def test_get_number_of_atoms_in_reaction_zone(self):
+        """Test the get_number_of_atoms_in_reaction_zone() method."""
+        self.assertEqual(self.rxn1.get_number_of_atoms_in_reaction_zone(), 3)  # H_Abstraction
+        self.assertEqual(self.rxn2.get_number_of_atoms_in_reaction_zone(), 4)  # Disprop
+        self.assertEqual(self.rxn3.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn4.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn5.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn6.get_number_of_atoms_in_reaction_zone(), 4)  # Disprop
+        self.assertEqual(self.rxn7.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn8.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn9.get_number_of_atoms_in_reaction_zone(), 5)  # HO2_Elimination_from_PeroxyRadical
+        self.assertEqual(self.rxn10.get_number_of_atoms_in_reaction_zone(), 3)
+        self.assertEqual(self.rxn11.get_number_of_atoms_in_reaction_zone(), 3)
+
+    def test_get_atom_map(self):
+        """Test getting an atom map for a reaction"""
+
+        # 1. trivial unimolecular: H2O <=> H2O
+        h2o_xyz_1 = {'symbols': ('O', 'H', 'H'), 'isotopes': (16, 1, 1),
+                     'coords': ((-0.0003283189391273643, 0.39781490416473486, 0.0),
+                                (-0.7633034507689803, -0.19953755103743254, 0.0),
+                                (0.7636317697081081, -0.19827735312730177, 0.0))}
+        r_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_1)
+        p_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_1)
+        rxn_1 = ARCReaction(reactants=['H2O'], products=['H2O'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn_1.atom_map, [0, 1, 2])
+        self.assertTrue(check_atom_map(rxn_1))
+
+        # 2. trivial unimolecular with an intentional mixed atom order: H2O <=> H2O
+        h2o_xyz_2 = {'symbols': ('H', 'H', 'O'), 'isotopes': (1, 1, 16),
+                     'coords': ((-0.7633034507689803, -0.19953755103743254, 0.0),
+                                (0.7636317697081081, -0.19827735312730177, 0.0),
+                                (-0.0003283189391273643, 0.39781490416473486, 0.0))}
+        p_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_2)
+        rxn_2 = ARCReaction(reactants=['H2O'], products=['H2O'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn_2.atom_map, [2, 0, 1])
+        self.assertTrue(check_atom_map(rxn_2))
+
+        # 3. trivial bimolecular: H + CH3NH2 <=> H2 + CH2NH2
+        ch3nh2_xyz = {'coords': ((-0.5734111454228507, 0.0203516083213337, 0.03088703933770556),
+                                 (0.8105595891860601, 0.00017446498908627427, -0.4077728757313545),
+                                 (-1.1234549667791063, -0.8123899006368857, -0.41607711106038836),
+                                 (-0.6332220120842996, -0.06381791823047896, 1.1196983583774054),
+                                 (-1.053200912106195, 0.9539501896695028, -0.27567270246542575),
+                                 (1.3186422395164141, 0.7623906284020254, 0.038976118645639976),
+                                 (1.2540872076899663, -0.8606590725145833, -0.09003882710357966)),
+                      'isotopes': (12, 14, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'N', 'H', 'H', 'H', 'H', 'H')}
+        ch2nh2_xyz = {'coords': ((0.6919493009211066, 0.054389375309083846, 0.02065422596281878),
+                                 (1.3094508022837807, -0.830934909576592, 0.14456347719459348),
+                                 (1.1649142139806816, 1.030396183273415, 0.08526955368597328),
+                                 (-0.7278194451655412, -0.06628299353512612, -0.30657582460750543),
+                                 (-1.2832757211903472, 0.7307667658607352, 0.00177732009031573),
+                                 (-1.155219150829674, -0.9183344213315149, 0.05431124767380799)),
+                      'isotopes': (12, 1, 1, 14, 1, 1),
+                      'symbols': ('C', 'H', 'H', 'N', 'H', 'H')}
+        r_1 = ARCSpecies(label='H', smiles='[H]', xyz={'coords': ((0, 0, 0),), 'isotopes': (1,), 'symbols': ('H',)})
+        r_2 = ARCSpecies(label='CH3NH2', smiles='CN', xyz=ch3nh2_xyz)
+        p_1 = ARCSpecies(label='H2', smiles='[H][H]', xyz=self.h2_xyz)
+        p_2 = ARCSpecies(label='CH2NH2', smiles='[CH2]N', xyz=ch2nh2_xyz)
+        rxn_3 = ARCReaction(reactants=['H', 'CH3NH2'], products=['H2', 'CH2NH2'],
+                            r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn_3.family, "H_Abstraction")
+        self.assertIn(rxn_3.atom_map[0], [0, 1])
+        self.assertEqual(rxn_3.atom_map[1:3], [2, 5])
+        for index in [3, 4, 5]:
+            self.assertIn(rxn_3.atom_map[index], [0, 1, 3, 4])
+        self.assertIn(rxn_3.atom_map[6:], [[7, 6], [6, 7]])
+        self.assertTrue(check_atom_map(rxn_3))
+
+        # 4. trivial bimolecular in reverse order: H + CH3NH2 <=> CH2NH2 + H2
+        rxn_4 = ARCReaction(reactants=['H', 'CH3NH2'], products=['CH2NH2', 'H2'],
+                            r_species=[r_1, r_2], p_species=[p_2, p_1])
+        self.assertIn(rxn_4.atom_map[0], [6, 7])
+        self.assertEqual(rxn_4.atom_map[1:3], [0, 3])
+        for index in [3, 4, 5]:
+            self.assertIn(rxn_4.atom_map[index], [1, 2, 6, 7])
+        self.assertIn(rxn_4.atom_map[6:], [[5, 4], [4, 5]])
+        self.assertTrue(check_atom_map(rxn_4))
+
+        # H_Abstraction: C3H6O + C4H9O <=> C3H5O + C4H10O
+        c3h6o_xyz = {'coords': ((-1.0614352911982476, -0.35086070951203013, 0.3314546936475969),
+                                (0.08232694092180896, 0.5949821397504677, 0.020767511136565348),
+                                (1.319643623472743, -0.1238222051358961, -0.4579284002686819),
+                                (1.4145501246584122, -1.339374145335546, -0.5896335370976351),
+                                (-0.7813545474862899, -1.0625754884160945, 1.1151404910689675),
+                                (-1.3481804813952152, -0.9258389945508673, -0.5552942813558058),
+                                (-1.9370566523150816, 0.2087367432207233, 0.6743848589525232),
+                                (-0.2162279757671984, 1.3021306884228383, -0.7596873819624604),
+                                (0.35220978385921775, 1.1650050778348893, 0.9154971248602527),
+                                (2.1755244752498673, 0.5316168937214946, -0.6947010789813145)),
+                     'isotopes': (12, 12, 12, 16, 1, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'C', 'O', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c4h9o_xyz = {'coords': ((0.025711531222639566, 1.5002469234994276, -0.018809721320361607),
+                                (-0.2501237905589279, 2.283276320160058, 0.6795778782867752),
+                                (0.21710649528235348, 1.7701501165266882, -1.0518607878262018),
+                                (-0.1296127183749531, 0.05931626777072968, 0.3829802045651552),
+                                (-1.5215969202773243, -0.4341372833972907, -0.0024458040153687616),
+                                (0.954275466146204, -0.8261822387409435, -0.2512878552942834),
+                                (2.238645869558612, -0.5229077195628998, 0.2868843893740711),
+                                (-0.022719509344805086, 0.012299638536749403, 1.47391586262432),
+                                (-1.6734988982808552, -1.4656213151526711, 0.3333615031669381),
+                                (-1.6708084550075688, -0.40804497485420527, -1.0879383468423085),
+                                (-2.3005261427143897, 0.18308085969254126, 0.45923715033920876),
+                                (0.7583076310662862, -1.882720433150506, -0.04089782108496264),
+                                (0.9972006722528377, -0.7025586995487184, -1.3391950754631268),
+                                (2.377638769033351, 0.43380253822255727, 0.17647842348371048)),
+                     'isotopes': (12, 1, 1, 12, 12, 12, 16, 1, 1, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'H', 'H', 'C', 'C', 'C', 'O', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c3h5o_xyz = {'coords': ((-1.1339526749599567, -0.11366348271898848, -0.17361178233231772),
+                                (0.1315989608873882, 0.19315012600914244, 0.5375291058021542),
+                                (0.12186476447223683, 0.5479023323381329, 1.5587521800625246),
+                                (1.435623589506148, 0.026762256080503182, -0.11697684942586563),
+                                (1.5559845484585495, -0.3678359306766861, -1.2677014903374604),
+                                (-1.6836994309836657, -0.8907558916446712, 0.3657463577153353),
+                                (-1.7622426221647125, 0.7810307051429465, -0.21575166529131876),
+                                (-0.9704526962734873, -0.4619573344933834, -1.1970278328709658),
+                                (2.3052755610575106, 0.2853672199629854, 0.5090419766779545)),
+                     'isotopes': (12, 12, 1, 12, 16, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'H', 'C', 'O', 'H', 'H', 'H', 'H')}
+        c4h10o_xyz = {'coords': ((-1.0599869990613344, -1.2397714287161459, 0.010871360821665921),
+                                 (-0.15570197396874313, -0.0399426912154684, -0.2627503141760959),
+                                 (-0.8357120092418682, 1.2531917172190083, 0.1920887922885465),
+                                 (1.2013757682054618, -0.22681093996845836, 0.42106399857821075),
+                                 (2.0757871909243337, 0.8339710961541049, 0.05934908325727899),
+                                 (-1.2566363886319676, -1.3536924078596617, 1.082401336123387),
+                                 (-0.5978887839926055, -2.1649950925769703, -0.3492714363488459),
+                                 (-2.0220571570609596, -1.1266512469159389, -0.4999630281827645),
+                                 (0.0068492778433242255, 0.03845056912064928, -1.3453078463310726),
+                                 (-0.22527545723287978, 2.1284779433126504, -0.05264318253022085),
+                                 (-1.804297837475001, 1.3767516368254167, -0.30411519687565475),
+                                 (-1.0079707678533625, 1.2514371624519658, 1.2738106811073706),
+                                 (1.0967232048111195, -0.23572903005857432, 1.511374071529777),
+                                 (1.6637048773271081, -1.1686406202494035, 0.10718319440789557),
+                                 (2.9210870554073614, 0.6739533324768243, 0.512528859867013)),
+                      'isotopes': (12, 12, 12, 12, 16, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'O', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O', xyz=c3h6o_xyz)
+        r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO', xyz=c4h9o_xyz)
+        p_1 = ARCSpecies(label='C3H5O', smiles='C[CH]C=O', xyz=c3h5o_xyz)
+        p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO', xyz=c4h10o_xyz)
+        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
+        atom_map = rxn.atom_map
+        self.assertEqual(atom_map[0:4], [0, 1, 3, 4])
+        self.assertIn(atom_map[4], [5,6, 7])
+        self.assertIn(atom_map[5], [5,6, 7])
+        self.assertIn(atom_map[6], [5,6, 7])
+        self.assertIn(atom_map[7], [2, 14, 15, 16, 18, 19, 20])
+        self.assertIn(atom_map[8], [2, 14, 15, 16, 18, 19, 20])
+        self.assertTrue(any(entry == 2 for entry in [atom_map[7], atom_map[8]]))
+        self.assertEqual(atom_map[9], 8)
+        self.assertIn(atom_map[10], [9,11])
+        self.assertIn(atom_map[11], [14, 15, 16,18,19,20])
+        self.assertIn(atom_map[12], [14, 15, 16,18,19,20])
+        self.assertEqual(atom_map[13],10)
+        self.assertIn(atom_map[14], [9,11])
+        self.assertEqual(atom_map[15:17], [12,13])
+        self.assertEqual(atom_map[17],17)
+        self.assertIn(atom_map[18], [14, 15, 16,18,19,20])
+        self.assertIn(atom_map[19], [14, 15, 16,18,19,20])
+        self.assertIn(atom_map[20], [14, 15, 16,18,19,20])
+        self.assertIn(atom_map[21], [21,22])
+        self.assertIn(atom_map[22], [21,22])
+        self.assertEqual(atom_map[23],23)
+        self.assertTrue(check_atom_map(rxn))
+
+        # H_Abstraction: NH + N2H3 <=> NH2 + N2H2(T)
+        n2h3_xyz = {'coords': ((-0.470579649119187, 0.04999660847282449, 0.3054306465848634),
+                               (0.7822241718336367, -0.48270144244781193, -0.23341826421899858),
+                               (1.5677258653370059, 0.10203349472372605, 0.08145841384293159),
+                               (-0.6670140616222734, 0.9245291856920813, -0.1819911659528955),
+                               (-1.212356326429186, -0.5938578464408176, 0.028520369744099196)),
+                    'isotopes': (14, 14, 1, 1, 1),
+                    'symbols': ('N', 'N', 'H', 'H', 'H')}
+        nh2_xyz = {'coords': ((0.0001637451536497341, 0.4005949879135532, 0.0),
+                              (-0.8317092208339203, -0.19995756341639623, 0.0),
+                              (0.8315454756802706, -0.20063742449715688, 0.0)),
+                   'isotopes': (14, 1, 1),
+                   'symbols': ('N', 'H', 'H')}
+        n2h2_t_xyz = {'coords': ((0.5974274138372041, -0.41113104979405946, 0.08609839663782763),
+                                 (1.421955422639823, 0.19737093442024492, 0.02508578507394823),
+                                 (-0.5974274348582206, 0.41113108883884353, -0.08609846602622732),
+                                 (-1.4219554016188147, -0.19737097346502322, -0.02508571568554942)),
+                      'isotopes': (14, 1, 14, 1),
+                      'symbols': ('N', 'H', 'N', 'H')}
+        r_1 = ARCSpecies(label='NH', smiles='[NH]', xyz=self.nh_xyz)
+        r_2 = ARCSpecies(label='N2H3', smiles='N[NH]', xyz=n2h3_xyz)
+        p_1 = ARCSpecies(label='NH2', smiles='[NH2]', xyz=nh2_xyz)
+        p_2 = ARCSpecies(label='N2H2(T)', smiles='[NH][NH]', xyz=n2h2_t_xyz)
+        rxn = ARCReaction(reactants=['NH', 'N2H3'], products=['NH2', 'N2H2(T)'],
+                          r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[0], 0)
+        self.assertIn(rxn.atom_map[1], [1, 2])
+        self.assertIn(rxn.atom_map[2], [3, 5])
+        self.assertIn(rxn.atom_map[3], [3, 5])
+        self.assertIn(rxn.atom_map[4], [4, 6])
+        self.assertIn(rxn.atom_map[5], [1, 2, 4, 6])
+        self.assertIn(rxn.atom_map[6], [1, 2, 4, 6])
+        self.assertTrue(any(rxn.atom_map[index] in [1, 2] for index in [5, 6]))
+        self.assertTrue(check_atom_map(rxn))
+
+        # Cyclopentadiene_scission: C6H6 <=> C6H6_2
+        c6h6_a_xyz = {'coords': ((1.465264096022479, 0.3555098886638667, 0.15268159347190322),
+                                 (0.4583546746026421, 1.1352991023740606, -0.26555553330413073),
+                                 (-0.7550043760214846, 0.35970165318809594, -0.5698935045151712),
+                                 (-1.485327813119871, -0.35660657095915016, 0.46119177830578917),
+                                 (-0.3414477960946828, -1.060779229397218, -0.11686056681841692),
+                                 (0.9879417277856641, -1.006839916409751, 0.12489717473407935),
+                                 (2.4630837864551887, 0.6629994259328668, 0.4197578798464181),
+                                 (0.5110882588097015, 2.2100951208919897, -0.3734820378556644),
+                                 (-1.1192886361027838, 0.384286081689225, -1.5897813181530946),
+                                 (-2.453224961870327, -0.7758708758357847, 0.2158838729688473),
+                                 (-1.3859013659398718, -0.054382091828296085, 1.4971154213962072),
+                                 (1.6544624054733257, -1.8534125883098933, 0.0440452399232336)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c6h6_b_xyz = {'coords': ((-1.474267041853848, 0.27665693719971857, -0.31815898666696507),
+                                 (-0.25527025747758825, 1.1936776717612125, -0.2432148642540069),
+                                 (0.9917471212521393, 0.7578589393970138, 0.059037260524552534),
+                                 (1.2911962562420976, -0.6524103892231805, 0.34598643264742923),
+                                 (0.321535921890914, -1.5867102018006056, 0.32000545365633654),
+                                 (-0.9417407846918554, -1.043897260224426, -0.002820356559266387),
+                                 (-2.2262364004658077, 0.5956762298613206, 0.40890113659975075),
+                                 (-1.90597332290244, 0.31143075666839354, -1.3222845692785703),
+                                 (-0.4221153027089989, 2.2469871640348815, -0.4470234892644997),
+                                 (1.824518548011024, 1.4543788790156666, 0.0987362566117616),
+                                 (2.3174577767359237, -0.9162726684959432, 0.5791638390925197),
+                                 (0.4791474859684761, -2.637376058194065, 0.5216718868909702)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C6H6_1', smiles='C1=CC2CC2=C1', xyz=c6h6_a_xyz)
+        p_1 = ARCSpecies(label='C6H6_b', xyz=c6h6_b_xyz, adjlist="""multiplicity 1
+                                                                    1  C u0 p0 c0 {2,S} {6,S} {7,S} {8,S}
+                                                                    2  C u0 p0 c0 {1,S} {3,D} {9,S}
+                                                                    3  C u0 p0 c0 {2,D} {4,S} {10,S}
+                                                                    4  C u0 p0 c0 {3,S} {5,D} {11,S}
+                                                                    5  C u0 p0 c0 {4,D} {6,S} {12,S}
+                                                                    6  C u0 p1 c0 {1,S} {5,S}
+                                                                    7  H u0 p0 c0 {1,S}
+                                                                    8  H u0 p0 c0 {1,S}
+                                                                    9  H u0 p0 c0 {2,S}
+                                                                    10 H u0 p0 c0 {3,S}
+                                                                    11 H u0 p0 c0 {4,S}
+                                                                    12 H u0 p0 c0 {5,S}""")
+        rxn = ARCReaction(reactants=['C6H6_1'], products=['C6H6_b'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [1, 4, 2, 0, 5, 3, 10, 9, 8, 7, 6, 11])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Disproportionation: HO2 + NHOH <=> NH2OH + O2
+        nhoh_xyz = {'coords': ((0.5055094877826753, 0.03248552573561613, -0.443416250587286),
+                               (1.392367115364475, -0.021750569314658803, 0.07321920788090872),
+                               (-0.570163178752975, -0.035696714715839996, 0.48914535186936214),
+                               (-1.3277134243941644, 0.024961758294888944, -0.11894830916297996)),
+                    'isotopes': (14, 1, 16, 1), 'symbols': ('N', 'H', 'O', 'H')}
+        nh2oh_xyz = {'coords': ((-0.442357984214193, 0.12755746178283767, -0.283450834226086),
+                                (0.8066044298181865, -0.19499391813986608, 0.38695057103192726),
+                                (-0.9953709942529645, -0.7170738803381369, -0.11579136415085267),
+                                (-0.8349557675364339, 0.8418549600381088, 0.33540420712720587),
+                                (1.4660803161854115, -0.05734462334294334, -0.32311257978218827)),
+                     'isotopes': (14, 16, 1, 1, 1), 'symbols': ('N', 'O', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='NHOH', smiles='[NH]O', xyz=nhoh_xyz)
+        r_2 = ARCSpecies(label='HO2', smiles='O[O]', xyz=self.ho2_xyz)
+        p_1 = ARCSpecies(label='O2', smiles='[O][O]', xyz=self.o2_xyz)
+        p_2 = ARCSpecies(label='NH2OH', smiles='NO', xyz=nh2oh_xyz)
+        rxn = ARCReaction(reactants=['NHOH', 'HO2'], products=['O2', 'NH2OH'],
+                          r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[0], 2)
+        for index in [1, 6]:
+            self.assertIn(rxn.atom_map[index], [4, 5])
+        self.assertEqual(rxn.atom_map[2], 3)
+        self.assertEqual(rxn.atom_map[3], 6)
+        for index in [4, 5]:
+            self.assertIn(rxn.atom_map[index], [0, 1])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Intra_Disproportionation: C10H10_a <=> C10H10_b
+        c10h10_a_xyz = {'coords': ((3.1623638230700997, 0.39331289450005563, -0.031839117414963584),
+                                   (1.8784852381397288, 0.037685951926618944, -0.13659028131444134),
+                                   (0.9737380560194014, 0.5278617594060281, -1.1526858375270472),
+                                   (1.2607098516126556, 1.1809007875206383, -1.9621017164412065),
+                                   (-0.36396095305912823, -0.13214785064139675, -1.0200667625809143),
+                                   (-1.5172464644867296, 0.8364138939810618, -1.0669384323486588),
+                                   (-2.4922101649968655, 0.8316551483126366, -0.14124720277902958),
+                                   (-2.462598061982958, -0.09755474191953761, 0.9703503187569243),
+                                   (-1.4080417204047313, -0.8976377310686736, 1.1927020968566089),
+                                   (-0.27981087345916755, -0.8670643393461046, 0.29587765657632165),
+                                   (1.1395623815572733, -0.9147118621123697, 0.771368745020215),
+                                   (3.7901243915692864, -0.006544237180536178, 0.7580206603561134),
+                                   (3.6186251824572455, 1.0920401631166292, -0.725695658374561),
+                                   (-0.4799044636709365, -0.8577283498506146, -1.8345168113636874),
+                                   (-1.5704890060131314, 1.527002009812866, -1.902575985299536),
+                                   (-3.3260277144990296, 1.5238536460491903, -0.20338465526703625),
+                                   (-3.311126364299293, -0.09969554359088921, 1.6478137927333953),
+                                   (-1.3707042898204835, -1.549541647625315, 2.0589774409040964),
+                                   (1.5338362221707007, -1.9310023570889727, 0.6663504223502944),
+                                   (1.2246749300961473, -0.5970975942012858, 1.816181327157103)),
+                        'isotopes': (12, 12, 12, 1, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                        'symbols': ('C', 'C', 'C', 'H', 'C', 'C', 'C', 'C', 'C', 'C', 'C',
+                                    'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c10h10_b_xyz = {'coords': ((3.247237794328524, -0.13719671162966918, 0.19555833918937052),
+                                   (1.9094861712282774, -0.08067655688828143, 0.14898941432495702),
+                                   (0.9973729357914858, -1.2703386896415134, -0.09322848415119056),
+                                   (-0.37904449715218924, -0.6747166782032148, -0.049044448345326556),
+                                   (-0.32906812544096026, 0.704634441388649, 0.189424753183012),
+                                   (-1.4900181263846768, 1.4572613706024167, 0.2695747550348709),
+                                   (-2.715200996994148, 0.8069241052920498, 0.10660938013945513),
+                                   (-2.765284083663716, -0.5753713833636181, -0.13236922431004927),
+                                   (-1.5909002849280705, -1.3270914347507115, -0.21179882275795825),
+                                   (1.0862366144301145, 1.1823049698313937, 0.33079658088902575),
+                                   (3.8424769924852367, 0.7530758608805569, 0.37314678191170336),
+                                   (3.7762437608797406, -1.0749685445597326, 0.05710603017340202),
+                                   (1.1128196175313243, -2.0170485762246773, 0.6986324476157837),
+                                   (1.187449599052061, -1.7129398667445945, -1.0760419644685346),
+                                   (-1.453108430051206, 2.525963604437891, 0.45426129138400156),
+                                   (-3.639988653002051, 1.3756767310587803, 0.16518163487425436),
+                                   (-3.7283956370857467, -1.0643593255501977, -0.2566648708585298),
+                                   (-1.631427244782937, -2.3956407728893367, -0.3966116183664473),
+                                   (1.3188711462571718, 1.9143096670969255, -0.4489453399950017),
+                                   (1.2442414475018486, 1.6101977898569013, 1.3257284397785851)),
+                        'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                        'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C',
+                                    'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C10H10_a', smiles='C=C1[CH]C2C=CC=C[C]2C1', xyz=c10h10_a_xyz, multiplicity=3)
+        p_1 = ARCSpecies(label='C10H10_b', smiles='C=C1CC2=C(C=CC=C2)C1', xyz=c10h10_b_xyz)
+        rxn = ARCReaction(reactants=['C10H10_a'], products=['C10H10_b'],
+                          r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [0, 1, 8, 13, 3, 2, 7, 6, 5, 4, 9, 10, 17, 12, 11, 16, 15, 14, 19, 18])
+        self.assertTrue(check_atom_map(rxn))
+
+        # intra_NO2_ONO_conversion: C2H5NO2 <=> C2H5ONO
+        c6h5_xyz = {'coords': ((1.8953828083622057, 0.8695975650550358, 0.6461465212661076),
+                               (1.3601473931706598, -0.04212583715410005, 0.0034200061443233247),
+                               (1.8529583069008781, -0.6310931351538215, -0.9666668585141432),
+                               (-0.010154355673379136, -0.4652844276756663, 0.43320585211058743),
+                               (-1.0281604639422022, 0.36855062612122236, -0.3158851121891869),
+                               (-0.11071296591935365, -1.5314728469286516, 0.20909234121344752),
+                               (-0.07635985361458197, -0.31625218083177237, 1.5151037167736001),
+                               (-2.042322710601489, 0.08102183703582924, -0.021667016484293297),
+                               (-0.9033569412063314, 1.436005790671757, -0.10388682333330314),
+                               (-0.937421217476434, 0.23105260886017234, -1.3988626269871478)),
+                    'isotopes': (16, 14, 16, 12, 12, 1, 1, 1, 1, 1),
+                    'symbols': ('O', 'N', 'O', 'C', 'C', 'H', 'H', 'H', 'H', 'H')}
+        c7h5o_xyz = {'coords': ((-1.3334725178745668, 0.2849178019354427, 0.4149005134933577),
+                                (-0.08765353373275289, 0.24941420749682627, -0.4497882845360618),
+                                (1.0488580188184402, 0.3986394744609146, 0.39515448276833964),
+                                (2.2292240798482883, 0.36629637181188207, -0.4124684043339001),
+                                (3.2413605054484185, 0.4928521621538312, 0.283008378837631),
+                                (-1.3088339518827734, -0.5173661350567303, 1.1597967522753032),
+                                (-2.23462275856269, 0.17332354052924734, -0.19455307765792382),
+                                (-1.393828440234405, 1.2294860794610234, 0.9656140588162426),
+                                (-0.12370667081323389, 1.0672740524773998, -1.1795070012935482),
+                                (-0.037324731014725374, -0.7080479312151163, -0.9821574183694773)),
+                     'isotopes': (12, 12, 16, 14, 16, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'O', 'N', 'O', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C2H5NO2', smiles='[O-][N+](=O)CC', xyz=c6h5_xyz)
+        p_1 = ARCSpecies(label='C2H5ONO', smiles='CCON=O', xyz=c7h5o_xyz)
+        rxn = ARCReaction(reactants=['C2H5NO2'], products=['C2H5ONO'],
+                          r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [4, 3, 2, 1, 0, 8, 9, 6, 5, 7])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Disproportionation: C4H7 + O2 <=> HO2 + C4H6
+        c4h7_xyz = {'coords': ((-2.040921404503424, -0.12903384637698798, 0.1559892045303822),
+                               (-0.7546540332943176, -0.4098957103161423, -0.07681407943731554),
+                               (0.3137517227573887, 0.47379064315829633, 0.303025839828397),
+                               (0.09502978026667419, 1.3942096052269417, 0.834199535314798),
+                               (1.734012668678617, 0.08135386277553083, 0.0906583073064836),
+                               (-2.352694765027891, 0.7875623110661275, 0.6465408489803196),
+                               (-2.8196259554078997, -0.8225020395029484, -0.14562281062524043),
+                               (-0.49241522029670126, -1.3423933663677394, -0.5719234920796793),
+                               (2.1384679029944533, -0.37774268314938586, 0.9976275308860051),
+                               (2.3331746195641365, 0.9677350359207318, -0.13953736233285224),
+                               (1.8458746842689961, -0.623083812434417, -0.7393520512375593)),
+                    'isotopes': (12, 12, 12, 1, 12, 1, 1, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'C', 'H', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c4h6_xyz = {'coords': ((-1.1313721520581368, 0.4375787725187425, 1.3741095482244203),
+                               (-0.5236696446754213, -0.27046339876338915, 0.4152401808417905),
+                               (0.5236696150303143, 0.2704633473040529, -0.41524017130113694),
+                               (1.1313721685204072, -0.4375787650279751, -1.3741095524658273),
+                               (-0.8696512779281117, 1.4694838181320669, 1.5851480041034802),
+                               (-1.915706463982211, -0.010750118295295768, 1.9758596362701513),
+                               (-0.8263303869083625, -1.301920739528746, 0.24674332317151054),
+                               (0.8263303006084768, 1.3019207019374226, -0.24674330995607902),
+                               (1.9157064555415753, 0.010750214228214268, -1.9758596165946158),
+                               (0.8696513858514865, -1.469483832503432, -1.5851480422945032)),
+                    'isotopes': (12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C4H7', smiles='C=C[CH]C', xyz=c4h7_xyz)
+        r_2 = ARCSpecies(label='O2', smiles='[O][O]', xyz=self.o2_xyz)
+        p_1 = ARCSpecies(label='HO2', smiles='O[O]', xyz=self.ho2_xyz)
+        p_2 = ARCSpecies(label='C4H6', smiles='C=CC=C', xyz=c4h6_xyz)
+        rxn = ARCReaction(reactants=['C4H7', 'O2'], products=['HO2', 'C4H6'],
+                          r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[:5], [3, 4, 5, 10, 6])
+        self.assertIn(rxn.atom_map[5:7], [[8, 7], [7, 8]])
+        self.assertEqual(rxn.atom_map[7], 9)
+        self.assertIn(tuple(rxn.atom_map[8:11]), permutations([2, 11, 12]))
+        self.assertIn(tuple(rxn.atom_map[11:]), permutations([0, 1]))
+
+        # Disproportionation: HO2 + NHOH <=> NH2OH + O2
+        nhoh_xyz = {'coords': ((0.5055094877826753, 0.03248552573561613, -0.443416250587286),
+                               (1.392367115364475, -0.021750569314658803, 0.07321920788090872),
+                               (-0.570163178752975, -0.035696714715839996, 0.48914535186936214),
+                               (-1.3277134243941644, 0.024961758294888944, -0.11894830916297996)),
+                    'isotopes': (14, 1, 16, 1), 'symbols': ('N', 'H', 'O', 'H')}
+        nh2oh_xyz = {'coords': ((-0.442357984214193, 0.12755746178283767, -0.283450834226086),
+                                (0.8066044298181865, -0.19499391813986608, 0.38695057103192726),
+                                (-0.9953709942529645, -0.7170738803381369, -0.11579136415085267),
+                                (-0.8349557675364339, 0.8418549600381088, 0.33540420712720587),
+                                (1.4660803161854115, -0.05734462334294334, -0.32311257978218827)),
+                     'isotopes': (14, 16, 1, 1, 1), 'symbols': ('N', 'O', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='NHOH', smiles='[NH]O', xyz=nhoh_xyz)
+        r_2 = ARCSpecies(label='HO2', smiles='O[O]', xyz=self.ho2_xyz)
+        p_1 = ARCSpecies(label='O2', smiles='[O][O]', xyz=self.o2_xyz)
+        p_2 = ARCSpecies(label='NH2OH', smiles='NO', xyz=nh2oh_xyz)
+        rxn = ARCReaction(reactants=['NHOH', 'HO2'], products=['O2', 'NH2OH'],
+                          r_species=[r_1, r_2], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[0], 2)
+        for index in [1, 6]:
+            self.assertIn(rxn.atom_map[index], [4, 5])
+        self.assertEqual(rxn.atom_map[2], 3)
+        self.assertEqual(rxn.atom_map[3], 6)
+        for index in [4, 5]:
+            self.assertIn(rxn.atom_map[index], [0, 1])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Intra_Disproportionation: C10H10_a <=> C10H10_b
+        c10h10_a_xyz = {'coords': ((3.1623638230700997, 0.39331289450005563, -0.031839117414963584),
+                                   (1.8784852381397288, 0.037685951926618944, -0.13659028131444134),
+                                   (0.9737380560194014, 0.5278617594060281, -1.1526858375270472),
+                                   (1.2607098516126556, 1.1809007875206383, -1.9621017164412065),
+                                   (-0.36396095305912823, -0.13214785064139675, -1.0200667625809143),
+                                   (-1.5172464644867296, 0.8364138939810618, -1.0669384323486588),
+                                   (-2.4922101649968655, 0.8316551483126366, -0.14124720277902958),
+                                   (-2.462598061982958, -0.09755474191953761, 0.9703503187569243),
+                                   (-1.4080417204047313, -0.8976377310686736, 1.1927020968566089),
+                                   (-0.27981087345916755, -0.8670643393461046, 0.29587765657632165),
+                                   (1.1395623815572733, -0.9147118621123697, 0.771368745020215),
+                                   (3.7901243915692864, -0.006544237180536178, 0.7580206603561134),
+                                   (3.6186251824572455, 1.0920401631166292, -0.725695658374561),
+                                   (-0.4799044636709365, -0.8577283498506146, -1.8345168113636874),
+                                   (-1.5704890060131314, 1.527002009812866, -1.902575985299536),
+                                   (-3.3260277144990296, 1.5238536460491903, -0.20338465526703625),
+                                   (-3.311126364299293, -0.09969554359088921, 1.6478137927333953),
+                                   (-1.3707042898204835, -1.549541647625315, 2.0589774409040964),
+                                   (1.5338362221707007, -1.9310023570889727, 0.6663504223502944),
+                                   (1.2246749300961473, -0.5970975942012858, 1.816181327157103)),
+                        'isotopes': (12, 12, 12, 1, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                        'symbols': ('C', 'C', 'C', 'H', 'C', 'C', 'C', 'C', 'C', 'C', 'C',
+                                    'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c10h10_b_xyz = {'coords': ((3.247237794328524, -0.13719671162966918, 0.19555833918937052),
+                                   (1.9094861712282774, -0.08067655688828143, 0.14898941432495702),
+                                   (0.9973729357914858, -1.2703386896415134, -0.09322848415119056),
+                                   (-0.37904449715218924, -0.6747166782032148, -0.049044448345326556),
+                                   (-0.32906812544096026, 0.704634441388649, 0.189424753183012),
+                                   (-1.4900181263846768, 1.4572613706024167, 0.2695747550348709),
+                                   (-2.715200996994148, 0.8069241052920498, 0.10660938013945513),
+                                   (-2.765284083663716, -0.5753713833636181, -0.13236922431004927),
+                                   (-1.5909002849280705, -1.3270914347507115, -0.21179882275795825),
+                                   (1.0862366144301145, 1.1823049698313937, 0.33079658088902575),
+                                   (3.8424769924852367, 0.7530758608805569, 0.37314678191170336),
+                                   (3.7762437608797406, -1.0749685445597326, 0.05710603017340202),
+                                   (1.1128196175313243, -2.0170485762246773, 0.6986324476157837),
+                                   (1.187449599052061, -1.7129398667445945, -1.0760419644685346),
+                                   (-1.453108430051206, 2.525963604437891, 0.45426129138400156),
+                                   (-3.639988653002051, 1.3756767310587803, 0.16518163487425436),
+                                   (-3.7283956370857467, -1.0643593255501977, -0.2566648708585298),
+                                   (-1.631427244782937, -2.3956407728893367, -0.3966116183664473),
+                                   (1.3188711462571718, 1.9143096670969255, -0.4489453399950017),
+                                   (1.2442414475018486, 1.6101977898569013, 1.3257284397785851)),
+                        'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                        'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C',
+                                    'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C10H10_a', smiles='C=C1[CH]C2C=CC=C[C]2C1', xyz=c10h10_a_xyz, multiplicity=3)
+        p_1 = ARCSpecies(label='C10H10_b', smiles='C=C1CC2=C(C=CC=C2)C1', xyz=c10h10_b_xyz)
+        rxn = ARCReaction(reactants=['C10H10_a'], products=['C10H10_b'],
+                          r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [0, 1, 8, 13, 3, 2, 7, 6, 5, 4, 9, 10, 17, 12, 11, 16, 15, 14, 19, 18])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Cyclopentadiene_scission: C6H6 <=> C6H6_2
+        c6h6_a_xyz = {'coords': ((1.465264096022479, 0.3555098886638667, 0.15268159347190322),
+                                 (0.4583546746026421, 1.1352991023740606, -0.26555553330413073),
+                                 (-0.7550043760214846, 0.35970165318809594, -0.5698935045151712),
+                                 (-1.485327813119871, -0.35660657095915016, 0.46119177830578917),
+                                 (-0.3414477960946828, -1.060779229397218, -0.11686056681841692),
+                                 (0.9879417277856641, -1.006839916409751, 0.12489717473407935),
+                                 (2.4630837864551887, 0.6629994259328668, 0.4197578798464181),
+                                 (0.5110882588097015, 2.2100951208919897, -0.3734820378556644),
+                                 (-1.1192886361027838, 0.384286081689225, -1.5897813181530946),
+                                 (-2.453224961870327, -0.7758708758357847, 0.2158838729688473),
+                                 (-1.3859013659398718, -0.054382091828296085, 1.4971154213962072),
+                                 (1.6544624054733257, -1.8534125883098933, 0.0440452399232336)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c6h6_b_xyz = {'coords': ((-1.474267041853848, 0.27665693719971857, -0.31815898666696507),
+                                 (-0.25527025747758825, 1.1936776717612125, -0.2432148642540069),
+                                 (0.9917471212521393, 0.7578589393970138, 0.059037260524552534),
+                                 (1.2911962562420976, -0.6524103892231805, 0.34598643264742923),
+                                 (0.321535921890914, -1.5867102018006056, 0.32000545365633654),
+                                 (-0.9417407846918554, -1.043897260224426, -0.002820356559266387),
+                                 (-2.2262364004658077, 0.5956762298613206, 0.40890113659975075),
+                                 (-1.90597332290244, 0.31143075666839354, -1.3222845692785703),
+                                 (-0.4221153027089989, 2.2469871640348815, -0.4470234892644997),
+                                 (1.824518548011024, 1.4543788790156666, 0.0987362566117616),
+                                 (2.3174577767359237, -0.9162726684959432, 0.5791638390925197),
+                                 (0.4791474859684761, -2.637376058194065, 0.5216718868909702)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C6H6_1', smiles='C1=CC2CC2=C1', xyz=c6h6_a_xyz)
+        p_1 = ARCSpecies(label='C6H6_b', xyz=c6h6_b_xyz, adjlist="""multiplicity 1
+                                                                    1  C u0 p0 c0 {2,S} {6,S} {7,S} {8,S}
+                                                                    2  C u0 p0 c0 {1,S} {3,D} {9,S}
+                                                                    3  C u0 p0 c0 {2,D} {4,S} {10,S}
+                                                                    4  C u0 p0 c0 {3,S} {5,D} {11,S}
+                                                                    5  C u0 p0 c0 {4,D} {6,S} {12,S}
+                                                                    6  C u0 p1 c0 {1,S} {5,S}
+                                                                    7  H u0 p0 c0 {1,S}
+                                                                    8  H u0 p0 c0 {1,S}
+                                                                    9  H u0 p0 c0 {2,S}
+                                                                    10 H u0 p0 c0 {3,S}
+                                                                    11 H u0 p0 c0 {4,S}
+                                                                    12 H u0 p0 c0 {5,S}""")
+        rxn = ARCReaction(reactants=['C6H6_1'], products=['C6H6_b'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [1, 4, 2, 0, 5, 3, 10, 9, 8, 7, 6, 11])
+        self.assertTrue(check_atom_map(rxn))
+
+        # intra_NO2_ONO_conversion: C2H5NO2 <=> C2H5ONO
+        c6h5_xyz = {'coords': ((1.8953828083622057, 0.8695975650550358, 0.6461465212661076),
+                               (1.3601473931706598, -0.04212583715410005, 0.0034200061443233247),
+                               (1.8529583069008781, -0.6310931351538215, -0.9666668585141432),
+                               (-0.010154355673379136, -0.4652844276756663, 0.43320585211058743),
+                               (-1.0281604639422022, 0.36855062612122236, -0.3158851121891869),
+                               (-0.11071296591935365, -1.5314728469286516, 0.20909234121344752),
+                               (-0.07635985361458197, -0.31625218083177237, 1.5151037167736001),
+                               (-2.042322710601489, 0.08102183703582924, -0.021667016484293297),
+                               (-0.9033569412063314, 1.436005790671757, -0.10388682333330314),
+                               (-0.937421217476434, 0.23105260886017234, -1.3988626269871478)),
+                    'isotopes': (16, 14, 16, 12, 12, 1, 1, 1, 1, 1),
+                    'symbols': ('O', 'N', 'O', 'C', 'C', 'H', 'H', 'H', 'H', 'H')}
+        c7h5o_xyz = {'coords': ((-1.3334725178745668, 0.2849178019354427, 0.4149005134933577),
+                                (-0.08765353373275289, 0.24941420749682627, -0.4497882845360618),
+                                (1.0488580188184402, 0.3986394744609146, 0.39515448276833964),
+                                (2.2292240798482883, 0.36629637181188207, -0.4124684043339001),
+                                (3.2413605054484185, 0.4928521621538312, 0.283008378837631),
+                                (-1.3088339518827734, -0.5173661350567303, 1.1597967522753032),
+                                (-2.23462275856269, 0.17332354052924734, -0.19455307765792382),
+                                (-1.393828440234405, 1.2294860794610234, 0.9656140588162426),
+                                (-0.12370667081323389, 1.0672740524773998, -1.1795070012935482),
+                                (-0.037324731014725374, -0.7080479312151163, -0.9821574183694773)),
+                     'isotopes': (12, 12, 16, 14, 16, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'O', 'N', 'O', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C2H5NO2', smiles='[O-][N+](=O)CC', xyz=c6h5_xyz)
+        p_1 = ARCSpecies(label='C2H5ONO', smiles='CCON=O', xyz=c7h5o_xyz)
+        rxn = ARCReaction(reactants=['C2H5NO2'], products=['C2H5ONO'],
+                          r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [4, 3, 2, 1, 0, 8, 9, 6, 5, 7])
+        self.assertTrue(check_atom_map(rxn))
+
+        # 1,2-Birad_to_alkene: SO2(T) => SO2(S)
+        # This test fails due to a problem in xyz perception of SO2(T).
+        so2_t_xyz = {'coords': ((0.02724478716956233, 0.6093829407458188, 0.0),
+                                (-1.3946381818031768, -0.24294788636871906, 0.0),
+                                (1.3673933946336125, -0.36643505437710233, 0.0)),
+                     'isotopes': (32, 16, 16), 'symbols': ('S', 'O', 'O')}
+        so2_s_xyz = {'coords': ((-1.3554230894998571, -0.4084942756329785, 0.0),
+                                (-0.04605352293144468, 0.6082507106551855, 0.0),
+                                (1.4014766124312934, -0.19975643502220325, 0.0)),
+                     'isotopes': (16, 32, 16), 'symbols': ('O', 'S', 'O')}
+
+        r_1 = ARCSpecies(label='SO2(T)', smiles='O=[S][O]', multiplicity=3, xyz=so2_t_xyz)
+        p_1 = ARCSpecies(label='SO2(S)', smiles='O=S=O', multiplicity=1, xyz=so2_s_xyz)
+        rxn = ARCReaction(reactants=['SO2(T)'], products=['SO2(S)'], r_species=[r_1], p_species=[p_1])
+        self.assertEqual(rxn.atom_map[0], 1)
+        self.assertTrue(check_atom_map(rxn))
+        # F[C]F + [CH3] <=> F[C](F)C
+        r1_xyz = {'symbols': ('F', 'C', 'F'),
+                  'isotopes': (19, 12, 19),
+                  'coords': ((-1.304203748543047, 0.3204330512721478, 0.0),
+                             (-1.9140293120972295e-09, -6.455569423898419e-09, 0.0),
+                             (1.304203750457077, -0.32043304481658, 0.0))}
+        r2_xyz = {'symbols': ('C', 'H', 'H', 'H'),
+                  'isotopes': (12, 1, 1, 1),
+                  'coords': ((3.3746019998564553e-09, 5.828827384106545e-09, -4.859105107686622e-09),
+                             (1.0669051052331406, -0.17519582095514982, 0.05416492980439295),
+                             (-0.6853171627400634, -0.8375353626879753, -0.028085652887100996),
+                             (-0.3815879458676787, 1.0127311778142964, -0.026079272058187608))}
+        p1_xyz = {'symbols': ('F', 'C', 'F', 'C', 'H', 'H', 'H'),
+                  'isotopes': (19, 12, 19, 12, 1, 1, 1),
+                  'coords': ((1.119619553527753, 1.4683016995266238, -0.4256355476700406),
+                             (0.7853078782246593, 0.21618941405118694, -0.04988462642839442),
+                             (1.7521918404307653, -0.6690180410121276, 0.2699297634217041),
+                             (-0.6404114764644544, -0.17821988481768988, 0.034782780206236624),
+                             (-0.7526348686344194, -1.2468644821661592, -0.16730131057453498),
+                             (-1.2335484316315908, 0.3780341245687702, -0.6961093474225755),
+                             (-1.0305244954526513, 0.03157716984946183, 1.0342182884675877))}
+        rxn = ARCReaction(r_species=[ARCSpecies(label="r1", smiles="F[C]F", xyz=r1_xyz),
+                                     ARCSpecies(label="r2", smiles="[CH3]", xyz=r2_xyz)],
+                          p_species=[ARCSpecies(label="p1", smiles="F[C](F)C", xyz=p1_xyz)])
+        self.assertIn(rxn.atom_map[:2], [[0, 1], [1, 0]])
+        self.assertEqual(rxn.atom_map[2], 2)
+        self.assertEqual(rxn.atom_map[3], 3)
+        self.assertIn(tuple(rxn.atom_map[4:]), list(permutations([4, 5, 6])))
+        self.assertTrue(check_atom_map(rxn))
+
+        # 1,2_NH3_elimination: NCC <=> C2H4 + NH3
+        ncc_xyz = {'coords': ((1.1517341397735719, -0.37601689454792764, -0.5230788502681245),
+                              (0.2893395715754821, 0.449973844025586, 0.3114935868175311),
+                              (-1.1415136758153028, -0.05605900830417449, 0.25915656466172177),
+                              (1.1385906595862103, -1.3375972344465683, -0.18540144244632334),
+                              (2.115146540825731, -0.05549033543399281, -0.4352422172888292),
+                              (0.6517228987651973, 0.4341829477365257, 1.3446618712379401),
+                              (0.32794656354609036, 1.4855039198343405, -0.04141588729000556),
+                              (-1.2132836539673237, -1.083868352883045, 0.6307611987658565),
+                              (-1.7869541982465666, 0.5726121409749625, 0.8809463351815471),
+                              (-1.5327288460430881, -0.03324102695569548, -0.763616120234416)),
+                   'isotopes': (14, 12, 12, 1, 1, 1, 1, 1, 1, 1),
+                   'symbols': ('N', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c2h4_xyz = {'coords': ((0.6664040429179742, 0.044298334171779405, -0.0050238049104911735),
+                               (-0.6664040438461246, -0.04429833352898575, 0.00502380522486473),
+                               (1.1686968388986039, 0.8743086488169786, -0.4919298928897832),
+                               (1.2813853343929593, -0.7114426553520238, 0.4734595111827543),
+                               (-1.2813853352424778, 0.7114426574294024, -0.4734595076873365),
+                               (-1.1686968371212578, -0.8743086515369692, 0.49192988907998186)),
+                    'isotopes': (12, 12, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'H', 'H', 'H', 'H')}
+        nh3_xyz = {'coords': ((0.0006492354002636227, -0.0009969784288894215, 0.2955929244020652),
+                              (-0.4178660616416419, 0.842103963871788, -0.09477452075659776),
+                              (-0.5203922802597125, -0.7822529247012627, -0.10002797449860866),
+                              (0.9376091065010891, -0.05885406074163403, -0.10079042914685925)),
+                   'isotopes': (14, 1, 1, 1),
+                   'symbols': ('N', 'H', 'H', 'H')}
+
+        r_1 = ARCSpecies(label='NCC', smiles='NCC', xyz=ncc_xyz)
+        p_1 = ARCSpecies(label='C2H4', smiles='C=C', xyz=c2h4_xyz)
+        p_2 = ARCSpecies(label='NH3', smiles='N', xyz=nh3_xyz)
+        rxn = ARCReaction(reactants=['NCC'], products=['C2H4', 'NH3'], r_species=[r_1], p_species=[p_1, p_2])
+        self.assertEqual(rxn.atom_map[0], 6)
+        self.assertIn(rxn.atom_map[1:3], [[1, 0], [0, 1]])
+        self.assertIn(tuple(rxn.atom_map[3:5]+[rxn.atom_map[7]]), permutations([7, 8, 9]))
+        self.assertIn(tuple(rxn.atom_map[5:7]+rxn.atom_map[8:]), permutations([2, 3, 4, 5]))
+        self.assertTrue(check_atom_map(rxn))
+
+        # 1+2_Cycloaddition: CH2 + C2H4 <=> C3H6
+        c2h4_xyz = {'coords': ((0.6664040429179742, 0.044298334171779405, -0.0050238049104911735),
+                               (-0.6664040438461246, -0.04429833352898575, 0.00502380522486473),
+                               (1.1686968388986039, 0.8743086488169786, -0.4919298928897832),
+                               (1.2813853343929593, -0.7114426553520238, 0.4734595111827543),
+                               (-1.2813853352424778, 0.7114426574294024, -0.4734595076873365),
+                               (-1.1686968371212578, -0.8743086515369692, 0.49192988907998186)),
+                    'isotopes': (12, 12, 1, 1, 1, 1), 'symbols': ('C', 'C', 'H', 'H', 'H', 'H')}
+        c_c3h6_xyz = {'coords': ((0.7868661913782324, -0.3644249639827158, -0.016337299842911886),
+                                 (-0.07793785747147405, 0.8603229755261934, 0.07746513362297117),
+                                 (-0.708928275400647, -0.4958980792223481, -0.06112784358024908),
+                                 (1.339749295484817, -0.5278616711993785, -0.9341881111902739),
+                                 (1.3001119953298585, -0.6947493102195698, 0.8793780279658545),
+                                 (-0.15055582331881673, 1.3597070015370083, 1.0367271647162946),
+                                 (-0.11091839380255, 1.5265948517709569, -0.7768389650606503),
+                                 (-1.1693748373792934, -0.7484015319217499, -1.0093221066790388),
+                                 (-1.2090122948201234, -0.9152892722884018, 0.8042440000480116)),
+                      'isotopes': (12, 12, 12, 1, 1, 1, 1, 1, 1), 'symbols': ('C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H')}
+
+        r_1 = ARCSpecies(label='CH2', xyz=self.ch2_xyz, adjlist="""1 C u0 p1 c0 {2,S} {3,S}
+                                                                   2 H u0 p0 c0 {1,S}
+                                                                   3 H u0 p0 c0 {1,S}""")
+        r_2 = ARCSpecies(label='C2H4', smiles='C=C', xyz=c2h4_xyz)
+        p_1 = ARCSpecies(label='cC3H6', smiles='C1CC1', xyz=c_c3h6_xyz)
+        rxn = ARCReaction(reactants=['CH2', 'C2H4'], products=['cC3H6'], r_species=[r_1, r_2], p_species=[p_1])
+        for index in [0, 3, 4]:
+            self.assertIn(rxn.atom_map[index], [0, 1, 2])
+        for index in [1, 2, 5, 6, 7, 8]:
+            self.assertIn(rxn.atom_map[index], [3, 4, 5, 6, 7, 8])
+        self.assertTrue(check_atom_map(rxn))
+
+        # 1,2_Insertion_CO: C4H10 + CO <=> C5H10O
+        c4h10_xyz = {'coords': ((-0.5828455298013108, 1.3281531294599287, -0.04960015063595639),
+                                (0.20452033859928953, 0.05503751610159247, -0.351590668388836),
+                                (1.2187217734495472, -0.22435034939324036, 0.7553438935018645),
+                                (-0.7402757883531311, -1.131897259046642, -0.526270047908048),
+                                (-1.149632334529979, 1.2345299096044358, 0.8830543278319224),
+                                (-1.2910247691071444, 1.5474495198220646, -0.8556442099189145),
+                                (0.08958996004802251, 2.187049294072444, 0.047578963870699015),
+                                (0.7510696374695547, 0.20211678856476709, -1.2911649516059494),
+                                (1.9161788635733445, 0.6129834282608764, 0.8637033961259424),
+                                (0.723393227383255, -0.37955365746174813, 1.7199258030015812),
+                                (1.8052293751859985, -1.1207509229675587, 0.5277678765569422),
+                                (-1.4506401201091412, -0.9467671747910582, -1.3389353480864132),
+                                (-1.31330819789714, -1.3230974306153704, 0.3874767468986707),
+                                (-0.18097643591114793, -2.04090279161046, -0.7716456312435797)),
+                     'isotopes': (12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c5h10o_xyz = {'coords': ((1.4311352287218408, -0.1713595727440808, -0.4215888483848517),
+                                 (-0.007186117613478591, 0.06984820110647515, 0.04712543561838732),
+                                 (-0.9581449869575146, 0.0768516496023853, -1.153820345745391),
+                                 (-0.42459441572492335, -1.0196556708425513, 1.0398144790596706),
+                                 (-0.06395445555126768, 1.4459669990683603, 0.6988370467311186),
+                                 (-0.39842691952831133, 1.6544415349370807, 1.860895997103657),
+                                 (1.7538538399565853, 0.5988164487250668, -1.1317944597170102),
+                                 (1.5308761668570723, -1.1450780226312873, -0.9137377478255552),
+                                 (2.130467943093651, -0.145756780679422, 0.4221764324976206),
+                                 (-1.9882342251557934, 0.2821166362714845, -0.8400630940054319),
+                                 (-0.6807867076715277, 0.8517398665867646, -1.8779276281234922),
+                                 (-0.9490513003000888, -0.8874499123119038, -1.6737493906621435),
+                                 (0.23329847490706446, -1.0315570674753483, 1.9164599735169805),
+                                 (-0.3863240121264062, -2.0126378831961222, 0.578337115559457),
+                                 (-1.4463966539332702, -0.8570614833514035, 1.4016914821743647),
+                                 (0.22346814102625032, 2.2907750569345855, 0.04734355220249537)),
+                      'isotopes': (12, 12, 12, 12, 12, 16, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'O', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C4H10', smiles='CC(C)C', xyz=c4h10_xyz)
+        r_2 = ARCSpecies(label='CO', smiles='[C-]#[O+]', xyz=self.co_xyz)
+        p_1 = ARCSpecies(label='C5H10O', smiles='CC(C)(C)C=O', xyz=c5h10o_xyz)
+        rxn = ARCReaction(reactants=['C4H10', 'CO'], products=['C5H10O'],
+                          r_species=[r_1, r_2], p_species=[p_1])
+        atom_map = rxn.atom_map
+        self.assertEqual(atom_map[:4], [0, 1, 2, 3])
+        self.assertIn(tuple(rxn.atom_map[4:7]), permutations([6, 7, 8]))
+        self.assertEqual(atom_map[7], 15)
+        self.assertIn(tuple(rxn.atom_map[8:11]), permutations([9, 10, 11]))
+        self.assertIn(tuple(rxn.atom_map[11:14]), permutations([12, 13, 14]))
+        self.assertEqual(atom_map[14:], [4, 5])
+        self.assertTrue(check_atom_map(rxn))
+        # same reaction in reverse:
+        rxn_rev = ARCReaction(r_species=[p_1], p_species=[r_1, r_2])
+        atom_map = rxn_rev.atom_map
+        for index in [0, 2, 3]:
+            self.assertIn(atom_map[index], [0, 2, 3])
+        self.assertEqual(atom_map[1], 1)
+        self.assertEqual(atom_map[4], 14)
+        self.assertEqual(atom_map[5], 15)
+        self.assertEqual(atom_map[15], 7)
+        self.assertTrue(check_atom_map(rxn_rev))
+
+        # Diels_alder_addition: C5H8 + C6H10 <=> C11H18
+        c5h8_xyz = {'coords': ((2.388426506127341, -0.6020682478448856, -0.8986239521455471),
+                               (1.396815470095451, 0.2559764141247285, -0.632876393172657),
+                               (0.15313289103802616, -0.14573699483201027, -0.021031021618524288),
+                               (-0.8389550397179193, 0.7169723970589436, 0.24404493146763848),
+                               (-2.134416163598417, 0.3239681447826502, 0.876570575233924),
+                               (2.3152942675091053, -1.659966892807757, -0.6677097540505594),
+                               (3.307483005086718, -0.2549641760041707, -1.3602353900805908),
+                               (1.5244650427331894, 1.3064325129702357, -0.885889345476673),
+                               (0.03466763777311284, -1.1983886005211812, 0.22843510909849465),
+                               (-0.7292165776910954, 1.7707854265126919, -0.0018778749819206306),
+                               (-2.2727957408233483, 0.8723614467877541, 1.8133393569164875),
+                               (-2.964923876317021, 0.5697550629604972, 0.20779128725191479),
+                               (-2.179977422215191, -0.7469982986693162, 1.0980624715582143)),
+                    'isotopes': (12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c6h10_xyz = {'coords': ((-3.1580683741393027, 0.12435732050743648, 0.062246914825226686),
+                                (-1.7707067002277326, -0.16620360178113405, 0.5349691635238483),
+                                (-0.6661431116320429, 0.14509293595419076, -0.15922278773395507),
+                                (0.6661430871150528, -0.14509454337155672, 0.31675535258860427),
+                                (1.7707067221399997, 0.1662031310249801, -0.37743578397831457),
+                                (3.158068300764984, -0.1243566042028104, 0.0952878105284522),
+                                (-3.168673040679144, 0.6195109523415628, -0.9138744940397917),
+                                (-3.725598607890039, -0.8074661408951581, -0.02161915764945937),
+                                (-3.667502866324593, 0.7743593207314634, 0.7801554985274884),
+                                (-1.689979340654408, -0.658941962521633, 1.5012451075034898),
+                                (-0.7566435422183935, 0.638020444531764, -1.1251628620848497),
+                                (0.7566435677358615, -0.6380221416323665, 1.2826952112274577),
+                                (1.6899798722782449, 0.6589420540549689, -1.3437113386443575),
+                                (3.667504053415929, -0.7743586338884942, -0.6226199722740314),
+                                (3.168672421569792, -0.6195094502282033, 1.0714098656973499),
+                                (3.7255975587458146, 0.8074669193750107, 0.17915450597834431)),
+                     'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c11h18_xyz = {'coords': ((-2.703705731925332, -1.6725650155987697, -0.8086740370494231),
+                                 (-1.5787486719767332, -0.9567028627407828, -0.9374280026568313),
+                                 (-1.0380952176862677, -0.018956959638684944, 0.13044184610143217),
+                                 (-0.9559942521379576, 1.4339345435700377, -0.4211901270741127),
+                                 (-1.0332585693389826, 2.4699679588763424, 0.7057994083773913),
+                                 (0.29330767863777807, 1.6799654965887798, -1.231863983890581),
+                                 (1.3587533124739988, 0.8659977820300574, -1.2254134762392683),
+                                 (1.4646089005142253, -0.38325835216422677, -0.38135979446817597),
+                                 (2.8541328762948206, -0.44094297285873296, 0.26496359509221906),
+                                 (0.34006414566475085, -0.47702332337899384, 0.6874327625078416),
+                                 (0.25971352010871435, -1.877767868723041, 1.3110012371667645),
+                                 (-3.0417827308140666, -2.322041441265777, -1.6103599735778764),
+                                 (-3.3090907216942607, -1.6304164329807997, 0.09119562710875757),
+                                 (-1.0140304257321437, -1.0355853116087828, -1.8648599111730466),
+                                 (-1.7519605248870382, -0.02119386222025415, 0.9668436940879309),
+                                 (-1.81873965484405, 1.6086866163315763, -1.078721360123664),
+                                 (-1.0435582627465962, 3.4878991458476953, 0.2994048809648787),
+                                 (-1.951192645793586, 2.339835712359188, 1.2889715104672264),
+                                 (-0.1829564138869207, 2.3964873273832725, 1.392011686068868),
+                                 (0.30323343644376083, 2.563802985828772, -1.8662760923115096),
+                                 (2.19957127963344, 1.1019579368769516, -1.875167073357893),
+                                 (1.38566629304311, -1.2380356901050797, -1.0661633096552972),
+                                 (3.643719857910847, -0.3537387754651392, -0.49036436481236706),
+                                 (2.9928305557668415, 0.3709281222195243, 0.9878133651866298),
+                                 (3.0131256633168944, -1.3901032201204848, 0.7853911163504533),
+                                 (0.5952865875235361, 0.20718050090958492, 1.5092530947735325),
+                                 (-0.5854224393429074, -1.9456691543733, 2.004496412992174),
+                                 (1.163930543826011, -2.107144483058995, 1.883011771518183),
+                                 (0.1405916116476466, -2.6554984025201795, 0.5498094976254133)),
+                      'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,
+                                   1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'H',
+                                  'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C5H8', smiles='C=CC=CC', xyz=c5h8_xyz)
+        r_2 = ARCSpecies(label='C6H10', smiles='CC=CC=CC', xyz=c6h10_xyz)
+        p_1 = ARCSpecies(label='C11H18', smiles='C=CC1C(C)C=CC(C)C1C', xyz=c11h18_xyz)
+        rxn = ARCReaction(reactants=['C5H8', 'C6H10'], products=['C11H18'], r_species=[r_1, r_2], p_species=[p_1])
+        atom_map = rxn.atom_map
+        self.assertEqual(atom_map[:5], [0, 1, 2, 9, 10])
+        self.assertEqual(atom_map[:5], [0, 1, 2, 9, 10])
+        self.assertIn(atom_map[5:7], [[11, 12], [12, 11]])
+        self.assertEqual(atom_map[7:10], [13, 14, 25])
+        self.assertIn(tuple(rxn.atom_map[10:13]), permutations([26, 27, 28]))
+        self.assertEqual(atom_map[13:19], [8, 7, 6, 5, 3, 4])
+        self.assertIn(tuple(rxn.atom_map[19:22]), permutations([24, 23, 22]))
+        self.assertEqual(atom_map[22:26], [21, 20, 19, 15])
+        self.assertIn(tuple(rxn.atom_map[26:]), permutations([16, 17, 18]))
+        self.assertTrue(check_atom_map(rxn))
+
+        # Intra_R_Add_Endocyclic: C9H15_a <=> C9H15_b
+        c9h15_a_xyz = {'coords': ((3.2994642637411093, -0.9763218631003405, -0.6681519125224107),
+                                  (2.092867397835492, -0.585345209944081, -1.094234941414971),
+                                  (1.1613654936979811, 0.23706312530825574, -0.350374400298155),
+                                  (1.4994958941811034, 0.8089206946686178, 0.9907635052181555),
+                                  (-0.2167854131709981, 0.47662057541684727, -0.9114032766325476),
+                                  (-1.2860618884154418, -0.32193095884739475, -0.1923953058559322),
+                                  (-1.2894939032313453, -1.8000285883092857, -0.4999462913608906),
+                                  (-2.2130886752718024, 0.1935684936507141, 0.6410238159619941),
+                                  (-2.383413365750594, 1.6157044776486373, 1.0712910920067213),
+                                  (3.696965023185511, -0.7025114561770845, 0.3028336703297904),
+                                  (3.9271105560154953, -1.5992344159626835, -1.2980759074189403),
+                                  (1.7682570069194234, -0.916244398055435, -2.0798789408635727),
+                                  (2.487309562171708, 1.280610628494466, 0.9837303428781683),
+                                  (1.4864744914143402, 0.025765724669991667, 1.7553223060895524),
+                                  (0.7820729499500115, 1.5805317186266579, 1.2867175051786177),
+                                  (-0.4230089341260823, 1.5513883408081797, -0.8834461827090913),
+                                  (-0.2525088519499385, 0.22261243999961292, -1.9790204993055305),
+                                  (-1.3684387790718693, -1.963416003052446, -1.5797964159431177),
+                                  (-2.1302956103647683, -2.3198259338415648, -0.028168861405248807),
+                                  (-0.3695265066561803, -2.2717068331186607, -0.14091188769329688),
+                                  (-2.9423489352590817, -0.48429745146049047, 1.0846035398328122),
+                                  (-1.6122780147641311, 2.2876041556921556, 0.691039744143378),
+                                  (-3.355397325714956, 1.9889012668068031, 0.7341417908661508),
+                                  (-2.358736435364993, 1.6715714700786672, 2.1643375109183345)),
+                       'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                       'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H', 'H',
+                                   'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        c9h15_b_xyz = {'coords': ((-2.5844283571790947, -1.0321735590817163, 0.6979015062994665),
+                                  (-1.7475791961733325, -0.06626031223098465, 1.0969062210689708),
+                                  (-0.6595890997866395, 0.44535980204779074, 0.19328352629720955),
+                                  (-1.2282980470691727, 1.3553131311426074, -0.9035809147486576),
+                                  (0.5116680348286848, 1.1207407424824027, 0.9673543663680071),
+                                  (1.4515588336620284, 0.3272984970368279, 0.15908291396837426),
+                                  (2.790359263734144, -0.07794911282678396, 0.6402051576162312),
+                                  (0.39868762752392606, -0.6378444769932384, -0.22420607008722174),
+                                  (0.4638588895257082, -1.0921494216349954, -1.67271225417489),
+                                  (-3.3702037268621954, -1.3885510696474426, 1.3571613514582264),
+                                  (-2.514756820219243, -1.4880585713706647, -0.2847299130808078),
+                                  (-1.8525509876151718, 0.37468306283449787, 2.084629086686036),
+                                  (-1.799839887685193, 2.183429924439949, -0.4685383552676342),
+                                  (-0.4353196261713602, 1.7968012774608193, -1.5175814720438623),
+                                  (-1.8935148835851774, 0.8013551257352, -1.5751801294655083),
+                                  (0.5782060423798034, 0.8980837541669382, 2.0389365697505366),
+                                  (0.6148811498579635, 2.2012663914014428, 0.8270631269396428),
+                                  (3.3879992933324807, 0.8037689675842231, 0.889705284982396),
+                                  (2.714060940989492, -0.70739197884347, 1.5320182978132968),
+                                  (3.3202001915969395, -0.6394149338748517, -0.13488149851161066),
+                                  (0.41364799755952236, -1.5167424973440258, 0.43811504056239386),
+                                  (0.5615949640204292, -0.25426187677410833, -2.3707422632792787),
+                                  (-0.44004933907211424, -1.649313877420301, -1.9393981990380054),
+                                  (1.3194067424075275, -1.7579889882901385, -1.8308113801134083)),
+                       'isotopes': (12, 12, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
+                       'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H',
+                                   'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C9H15_a', smiles='C=C[C](C)CC(C)=CC', xyz=c9h15_a_xyz)
+        p_1 = ARCSpecies(label='C9H15_b', smiles='C=CC1(C)C[C](C)C1C', xyz=c9h15_b_xyz)
+        rxn = ARCReaction(reactants=['C9H15_a'], products=['C9H15_b'],
+                          r_species=[r_1], p_species=[p_1])
+        atom_map = rxn.atom_map
+        self.assertEqual(atom_map[0:9], list(range(9)))
+        self.assertIn(atom_map[9:11], [[9, 10], [10, 9]])
+        self.assertEqual(atom_map[11], 11)
+        self.assertIn(tuple(rxn.atom_map[12:15]), permutations([13, 14, 12]))
+        self.assertIn(atom_map[15:17], [[15, 16], [16, 15]])
+        self.assertIn(tuple(rxn.atom_map[17:20]), permutations([18, 17, 19]))
+        self.assertEqual(atom_map[20], 20)
+        self.assertIn(tuple(rxn.atom_map[21:]), permutations([23, 21, 22]))
+        self.assertTrue(check_atom_map(rxn))
+
+        # R_Addition_COm: C6H5 + CO <=> C7H5O
+        c6h5_xyz = {'coords': ((0.1817676212163122, -1.6072341699404684, -0.014610043584505971),
+                               (1.3027386938520413, -0.7802649159703986, -0.0076490984025043415),
+                               (1.1475642728457944, 0.6058877336062989, 0.0049505291900821605),
+                               (-0.13153090866637432, 1.1630287566213553, 0.010572132054881396),
+                               (-1.2538945539777469, 0.33431084106618875, 0.0035960198829159064),
+                               (-1.0955796250821246, -1.0514866492107922, -0.009001872474708414),
+                               (2.2945290976411314, -1.222259069017827, -0.0120983109779029),
+                               (2.0221784174097133, 1.2509576921755168, 0.010380274196135802),
+                               (-0.25367929671488426, 2.243094989267151, 0.020390170037011494),
+                               (-2.250483228275848, 0.767769623706613, 0.007970374795096042),
+                               (-1.9636104902480103, -1.7038048323036503, -0.014500174716503693)),
+                    'isotopes': (12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1),
+                    'symbols': ('C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H')}
+        c7h5o_xyz = {'coords': ((3.6046073677554133, -0.5344883784336433, -0.4686416595112313),
+                                (2.450376918247941, -0.36333993603429526, -0.3185783842705891),
+                                (1.0452654391924683, -0.1549911825981301, -0.13589722616572933),
+                                (0.17928460434727675, -1.2499432760163112, -0.05142261213479038),
+                                (-1.1903765403115871, -1.0453466445053263, 0.1266843926255701),
+                                (-1.6956393825954146, 0.2514281313346147, 0.22045344560169716),
+                                (-0.83456152850501, 1.3456029168509482, 0.13658183163326776),
+                                (0.5355376113902255, 1.1439499192771787, -0.04151298496012599),
+                                (0.5636535723209614, -2.2654604192056556, -0.12342236998627074),
+                                (-1.863668502126327, -1.8967496276402949, 0.19236058875963039),
+                                (-2.762672022813616, 0.4096470069241553, 0.3591803505729345),
+                                (-1.2308445290855283, 2.355601612430931, 0.2099632744051463),
+                                (1.1990369921831652, 2.0040898776158196, -0.1057486465694942)),
+                     'isotopes': (16, 12, 12, 12, 12, 12, 12, 12, 1, 1, 1, 1, 1),
+                     'symbols': ('O', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H')}
+        r_1 = ARCSpecies(label='C6H5', smiles='[c]1ccccc1', xyz=c6h5_xyz)
+        r_2 = ARCSpecies(label='CO', smiles='[C-]#[O+]', xyz=self.co_xyz)
+        p_1 = ARCSpecies(label='C7H5O', smiles='O=[C]c1ccccc1', xyz=c7h5o_xyz)
+        rxn = ARCReaction(reactants=['C6H5', 'CO'], products=['C7H5O'],
+                          r_species=[r_1, r_2], p_species=[p_1])
+        self.assertEqual(rxn.atom_map, [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 0])
+        self.assertTrue(check_atom_map(rxn))
+
+        # Keto-enol isomerization: ch2choh <=> ch3cho
+        r_1 = ARCSpecies(label='CH2CHOH', smiles='C=CO', xyz=self.ch2choh_xyz)
+        p_1 = ARCSpecies(label='CH3CHO', smiles='CC=O', xyz=self.ch3cho_xyz)
+        rxn = ARCReaction(r_species=[r_1], p_species=[p_1])
+        atom_map = rxn.atom_map
+        self.assertTrue(check_atom_map(rxn))
+        self.assertTrue(atom_map[:3], [0, 1, 2])
+        self.assertIn(tuple(atom_map[3:5]+[atom_map[-1]]), permutations([3, 4, 5]))
+        self.assertEqual(atom_map[5], 6)
+
+    # Same species in products
+        rxn = ARCReaction(r_species=[ARCSpecies(label="r", smiles = 'C=C[CH]CC[CH]C=C')],
+                          p_species=[ARCSpecies(label="p1", smiles= 'C=CC=C'),
+                                     ARCSpecies(label="p2", smiles= 'C=CC=C')])
+        c_symmetry_h_1 = [1, 2, 11, 12]            # symmetry of carbons with one hydrogen
+        c_symmetry_h_2 = [0, 3, 10, 13]            # symmetry of carbons with two hydrogens
+        h_symmetry1 = [6, 7, 16, 17]               # symmetry of hydrogens with one other hydrogen second order neighbor
+        h_symmetry2 = [4, 5, 8, 9, 14 ,15, 18, 19] # symmetry of hydrogens with two other hydrogen second order neighbor
+        
+        label_species_atoms(rxn.r_species)
+        atom_map = rxn.atom_map
+        for atom in rxn.r_species[0].mol.copy(deep=True).atoms:
+            if atom.symbol == "C":
+                relevant_atom = atom
+            else:
+                relevant_atom = list(atom.bonds.keys())[0]
+            number_of_hydrogens = 0
+            for neighbor in relevant_atom.bonds.keys():
+                if neighbor.symbol=="H":
+                    number_of_hydrogens+=1
+            if number_of_hydrogens == 1:
+                self.assertIn(atom_map[int(atom.label)], c_symmetry_h_1 if atom.symbol == "C" else h_symmetry1)
+            else:
+                self.assertIn(atom_map[int(atom.label)], c_symmetry_h_2 if atom.symbol == "C" else h_symmetry2)
+        self.assertTrue(check_atom_map(rxn=rxn))
+
+    def test_mapping_XY_elimination_hydroxyl(self):
+        """Test mapping of a reaction family XY_elimination_hydroxyl"""    
+        rxn = ARCReaction(r_species=[ARCSpecies(label="r", smiles = 'O=C(O)CCF')],
+                          p_species=[ARCSpecies(label="p1", smiles='C=C'),
+                                     ARCSpecies(label="p2", smiles="F"),
+                                     ARCSpecies(label="p3", smiles="O=C=O")])
+        # if not rxn.family:  # reaction family not found for some reason.
+        #     rxn.family = "XY_elimination_hydroxyl"
+        atom_map = rxn.atom_map
+        self.assertIsNotNone(rxn.family)
+        self.assertTrue(check_atom_map(rxn=rxn))
+        self.assertIn(atom_map[:3], [[8, 9, 10], [10, 9, 8]])
+        self.assertIn(atom_map[3:5], [[0, 1], [1, 0]])
+        self.assertEqual(atom_map[5:7], [6, 7])
+        self.assertIn(atom_map[7:9], [[4, 5], [5, 4]])
+        self.assertIn(atom_map[9:], [[2, 3], [3, 2]])
+
+    def test_get_reactants_xyz(self):
+        """Test getting a combined string/dict representation of the cartesian coordinates of all reactant species"""
+        ch3nh2_xyz = {'coords': ((-0.5734111454228507, 0.0203516083213337, 0.03088703933770556),
+                                 (0.8105595891860601, 0.00017446498908627427, -0.4077728757313545),
+                                 (-1.1234549667791063, -0.8123899006368857, -0.41607711106038836),
+                                 (-0.6332220120842996, -0.06381791823047896, 1.1196983583774054),
+                                 (-1.053200912106195, 0.9539501896695028, -0.27567270246542575),
+                                 (1.3186422395164141, 0.7623906284020254, 0.038976118645639976),
+                                 (1.2540872076899663, -0.8606590725145833, -0.09003882710357966)),
+                      'isotopes': (12, 14, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'N', 'H', 'H', 'H', 'H', 'H')}
+        ch2nh2_xyz = {'coords': ((0.6919493009211066, 0.054389375309083846, 0.02065422596281878),
+                                 (1.3094508022837807, -0.830934909576592, 0.14456347719459348),
+                                 (1.1649142139806816, 1.030396183273415, 0.08526955368597328),
+                                 (-0.7278194451655412, -0.06628299353512612, -0.30657582460750543),
+                                 (-1.2832757211903472, 0.7307667658607352, 0.00177732009031573),
+                                 (-1.155219150829674, -0.9183344213315149, 0.05431124767380799)),
+                      'isotopes': (12, 1, 1, 14, 1, 1),
+                      'symbols': ('C', 'H', 'H', 'N', 'H', 'H')}
+        r_1 = ARCSpecies(label='H', smiles='[H]', xyz={'coords': ((0, 0, 0),), 'isotopes': (1,), 'symbols': ('H',)})
+        r_2 = ARCSpecies(label='CH3NH2', smiles='CN', xyz=ch3nh2_xyz)
+        p_1 = ARCSpecies(label='H2', smiles='[H][H]', xyz=self.h2_xyz)
+        p_2 = ARCSpecies(label='CH2NH2', smiles='[CH2]N', xyz=ch2nh2_xyz)
+        rxn_1 = ARCReaction(reactants=['H', 'CH3NH2'], products=['H2', 'CH2NH2'],
+                            r_species=[r_1, r_2], p_species=[p_1, p_2])
+        reactants_xyz_str = rxn_1.get_reactants_xyz()
+        reactants_xyz_dict = rxn_1.get_reactants_xyz(return_format='dict')
+        expected_reactants_xyz_str = """H      -0.33027713    0.00000000    0.00000000
+C      -0.69896689    0.01307198    0.19065646
+N       0.68500384   -0.00710516   -0.24800345
+H      -1.24901071   -0.81966953   -0.25630769
+H      -0.75877776   -0.07109755    1.27946778
+H      -1.17875666    0.94667056   -0.11590328
+H       1.19308649    0.75511100    0.19874554
+H       1.12853146   -0.86793870    0.06973060"""
+        expected_reactants_xyz_dict = {'symbols': ('H', 'C', 'N', 'H', 'H', 'H', 'H', 'H'),
+                                       'isotopes': (1, 12, 14, 1, 1, 1, 1, 1),
+                                       'coords': ((-0.33027712709756146, 0.0, 0.0),
+                                                  (-0.6989668914012913, 0.013071980537625375, 0.19065646408548476),
+                                                  (0.6850038432076193, -0.007105162794622051, -0.24800345098357532),
+                                                  (-1.2490107127575472, -0.8196695284205939, -0.25630768631260914),
+                                                  (-0.7587777580627403, -0.07109754601418727, 1.2794677831251846),
+                                                  (-1.1787566580846358, 0.9466705618857946, -0.11590327771764654),
+                                                  (1.1930864935379735, 0.7551110006183172, 0.19874554339341918),
+                                                  (1.1285314617115254, -0.8679387002982916, 0.06973059764419955))}
+        self.assertEqual(reactants_xyz_str, expected_reactants_xyz_str)
+        self.assertEqual(reactants_xyz_dict, expected_reactants_xyz_dict)
+
+        c2h5o3_xyz = {'coords': ((-1.3476727508427788, -0.49923624257482285, -0.3366372557370102),
+                                 (-0.11626816111736853, 0.3110915299407186, 0.018860985632263887),
+                                 (0.7531175607750088, 0.3366822240291409, -1.1050387236863213),
+                                 (0.5228736844989644, -0.3049881931104616, 1.1366016759286774),
+                                 (1.8270658637404131, 0.34102014147584997, 1.2684162942337813),
+                                 (-2.039181700362481, -0.5535509846570477, 0.5100031541057821),
+                                 (-1.865025875161301, -0.06806929272376178, -1.1994046923960628),
+                                 (-1.0711960095793496, -1.5264629385419055, -0.6002175107608478),
+                                 (-0.40133538695862053, 1.3357900487643664, 0.28224155088545305),
+                                 (1.3942569570346546, 1.035594500292526, -0.8890721851777293)),
+                      'isotopes': (12, 12, 16, 16, 16, 1, 1, 1, 1, 1),
+                      'symbols': ('C', 'C', 'O', 'O', 'O', 'H', 'H', 'H', 'H', 'H')}
+        c2h4o_xyz = {'coords': ((-0.6485165220711699, -0.036287809639473964, -0.040072327958319325),
+                                (0.8441328059817381, 0.04088405476411104, 0.05352861712992162),
+                                (1.4799812732494606, 1.0748679945888888, -0.1224478071645769),
+                                (-1.0603388058764294, 0.9464876376852732, -0.28238370478893315),
+                                (-0.9213427138232859, -0.7478396768473443, -0.8228167900899559),
+                                (-1.0499663443190728, -0.37234114306362315, 0.9187474043028493),
+                                (1.3560503068587568, -0.9057710574878411, 0.29544460856901716)),
+                     'isotopes': (12, 12, 16, 1, 1, 1, 1),
+                     'symbols': ('C', 'C', 'O', 'H', 'H', 'H', 'H')}
+        ho2_xyz = {'coords': ((0.0558910, -0.6204870, 0.0000000),
+                              (0.0558910, 0.7272050, 0.0000000),
+                              (-0.8942590, -0.8537420, 0.0000000)),
+                   'isotopes': (16, 16, 1),
+                   'symbols': ('O', 'O', 'H')}
+        r_1 = ARCSpecies(label='C2H5O3', smiles='CC(O)O[O]', xyz=c2h5o3_xyz)
+        p_1 = ARCSpecies(label='C2H4O', smiles='CC=O', xyz=c2h4o_xyz)
+        p_2 = ARCSpecies(label='HO2', smiles='O[O]', xyz=ho2_xyz)
+        rxn = ARCReaction(r_species=[r_1], p_species=[p_1, p_2])
+        self.assertIn(rxn.atom_map[0:5], [[0, 1, 2, 8, 7], [0, 1, 2, 7, 8]])
+        for index in [5, 6, 7]:
+            self.assertIn(rxn.atom_map[index], [3, 4, 5])
+        self.assertEqual(rxn.atom_map[8], 6)
+        self.assertEqual(rxn.atom_map[9], 9)
+        self.assertTrue(check_atom_map(rxn))
+
+    def test_get_single_mapped_product_xyz(self):
+        """Test the Reaction get_single_mapped_product_xyz() method"""
+        # Trivial unimolecular with an intentional mixed atom order: H2O <=> H2O
+        h2o_xyz_1 = """O      -0.00032832    0.39781490    0.00000000
+                       H      -0.76330345   -0.19953755    0.00000000
+                       H       0.76363177   -0.19827735    0.00000000"""
+        r_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_1)
+        h2o_xyz_2 = """H      -0.76330345   -0.19953755    0.00000000
+                       H       0.76363177   -0.19827735    0.00000000
+                       O      -0.00032832    0.39781490    0.00000000"""
+        p_1 = ARCSpecies(label='H2O', smiles='O', xyz=h2o_xyz_2)
+        rxn_1 = ARCReaction(reactants=['H2O'], products=['H2O'],
+                            r_species=[r_1], p_species=[p_1])
+        mapped_product = rxn_1.get_single_mapped_product_xyz()
+        self.assertEqual(rxn_1.atom_map, [2, 0, 1])
+        self.assertTrue(check_atom_map(rxn_1))
+        expected_xyz = {'symbols': ('O', 'H', 'H'), 'isotopes': (16, 1, 1),
+                        'coords': ((-0.00032832, 0.3978149, 0.0), (-0.76330345, -0.19953755, 0.0),
+                                   (0.76363177, -0.19827735, 0.0))}
+        self.assertEqual(mapped_product.get_xyz(), expected_xyz)
+
+        reactant_xyz = """C  -1.3087    0.0068    0.0318
+                          C   0.1715   -0.0344    0.0210
+                          N   0.9054   -0.9001    0.6395
+                          O   2.1683   -0.5483    0.3437
+                          N   2.1499    0.5449   -0.4631
+                          N   0.9613    0.8655   -0.6660
+                          H  -1.6558    0.9505    0.4530
+                          H  -1.6934   -0.0680   -0.9854
+                          H  -1.6986   -0.8169    0.6255"""
+        reactant = ARCSpecies(label='reactant', smiles='C([C]1=[N]O[N]=[N]1)', xyz=reactant_xyz)
+        product_xyz = """C  -1.0108   -0.0114   -0.0610
+                         C   0.4780    0.0191    0.0139
+                         N   1.2974   -0.9930    0.4693
+                         O   0.6928   -1.9845    0.8337
+                         N   1.7456    1.9701   -0.6976
+                         N   1.1642    1.0763   -0.3716
+                         H  -1.4020    0.9134   -0.4821
+                         H  -1.3327   -0.8499   -0.6803
+                         H  -1.4329   -0.1554    0.9349"""
+        product = ARCSpecies(label='product', smiles='[N-]=[N+]=C(N=O)C', xyz=product_xyz)
+        rxn_2 = ARCReaction(r_species=[reactant], p_species=[product])
+        self.assertTrue(check_atom_map(rxn_2))
+        mapped_product = rxn_2.get_single_mapped_product_xyz()
+        self.assertEqual(rxn_2.atom_map[:6], [0, 1, 2, 3, 4, 5])
+        self.assertIn(rxn_2.atom_map[6], [6, 8])
+        self.assertIn(rxn_2.atom_map[7], [6, 7])
+        self.assertIn(rxn_2.atom_map[8], [7, 8])
+        expected_xyz = {'symbols': ('C', 'C', 'N', 'O', 'N', 'N', 'H', 'H', 'H'),
+                        'isotopes': (12, 12, 14, 16, 14, 14, 1, 1, 1),
+                        'coords': ((-1.0108, -0.0114, -0.061), (0.478, 0.0191, 0.0139), (1.2974, -0.993, 0.4693),
+                                   (0.6928, -1.9845, 0.8337), (1.7456, 1.9701, -0.6976), (1.1642, 1.0763, -0.3716),
+                                   (-1.4329, -0.1554, 0.9349), (-1.402, 0.9134, -0.4821), (-1.3327, -0.8499, -0.6803))}
+        self.assertEqual(mapped_product.get_xyz(), expected_xyz)
+
+        reactant_xyz = """C  -1.3087    0.0068    0.0318
+                          C   0.1715   -0.0344    0.0210
+                          N   0.9054   -0.9001    0.6395
+                          O   2.1683   -0.5483    0.3437
+                          N   2.1499    0.5449   -0.4631
+                          N   0.9613    0.8655   -0.6660
+                          H  -1.6558    0.9505    0.4530
+                          H  -1.6934   -0.0680   -0.9854
+                          H  -1.6986   -0.8169    0.6255"""
+        reactant = ARCSpecies(label='reactant', smiles='C([C]1=[N]O[N]=[N]1)', xyz=reactant_xyz)
+        product_xyz = """C  -1.0108   -0.0114   -0.0610
+                         C   0.4780    0.0191    0.0139
+                         N   1.2974   -0.9930    0.4693
+                         O   0.6928   -1.9845    0.8337
+                         N   1.7456    1.9701   -0.6976
+                         N   1.1642    1.0763   -0.3716
+                         H  -1.4020    0.9134   -0.4821
+                         H  -1.3327   -0.8499   -0.6803
+                         H  -1.4329   -0.1554    0.9349"""
+        product = ARCSpecies(label='product', smiles='[N-]=[N+]=C(N=O)C', xyz=product_xyz)
+        rxn_2 = ARCReaction(r_species=[reactant], p_species=[product])
+        self.assertTrue(check_atom_map(rxn_2))
+        mapped_product = rxn_2.get_single_mapped_product_xyz()
+        self.assertEqual(rxn_2.atom_map[:6], [0, 1, 2, 3, 4, 5])
+        self.assertIn(rxn_2.atom_map[6], [6, 8])
+        self.assertIn(rxn_2.atom_map[7], [6, 7])
+        self.assertIn(rxn_2.atom_map[8], [7, 8])
+        expected_xyz = {'symbols': ('C', 'C', 'N', 'O', 'N', 'N', 'H', 'H', 'H'),
+                        'isotopes': (12, 12, 14, 16, 14, 14, 1, 1, 1),
+                        'coords': ((-1.0108, -0.0114, -0.061), (0.478, 0.0191, 0.0139), (1.2974, -0.993, 0.4693),
+                                   (0.6928, -1.9845, 0.8337), (1.7456, 1.9701, -0.6976), (1.1642, 1.0763, -0.3716),
+                                   (-1.4329, -0.1554, 0.9349), (-1.402, 0.9134, -0.4821), (-1.3327, -0.8499, -0.6803))}
+        self.assertEqual(mapped_product.get_xyz(), expected_xyz)
+
+    def test_check_attributes(self):
+        """Test checking the reaction attributes"""
+        rxn_1 = ARCReaction(label='H + [O-][N+](=N)N=O <=> [N-]=[N+](N=O)[O] + H2',
+                            r_species=[ARCSpecies(label='H', smiles='[H]'),
+                                       ARCSpecies(label='[O-][N+](=N)N=O', smiles='[O-][N+](=N)N=O')],
+                            p_species=[ARCSpecies(label='H2', smiles='[H][H]'),
+                                       ARCSpecies(label='[N-]=[N+](N=O)[O]', smiles='[N-]=[N+](N=O)[O]')],
+                            )
+        rxn_1.check_attributes()
+        self.assertEqual(rxn_1.reactants, ['H', '[O-][Np][=N]N=O'])
+        self.assertEqual(rxn_1.products, ['H2', '[N-]=[Np][N=O][O]'])
+        self.assertEqual(rxn_1.r_species[1].label, '[O-][Np][=N]N=O')
+
+    def test_remove_dup_species(self):
+        """Test the remove_dup_species function"""
+        species_list = [ARCSpecies(label='OH', smiles='[OH]'),
+                        ARCSpecies(label='OH', smiles='[OH]'),
+                        ARCSpecies(label='H', smiles='[H]'),
+                        ARCSpecies(label='H', smiles='[H]'),
+                        ARCSpecies(label='H2O', smiles='O'),
+                        ]
+        new_species_list = remove_dup_species(species_list=species_list)
+        self.assertEqual(len(new_species_list), 3)
+
+    def test_check_done_opt_r_n_p(self):
+        """Test the check_done_opt_r_n_p() method"""
+        c3_1_path = os.path.join(ARC_PATH, 'arc', 'testing', 'yml_testing', 'C3_1.yml')  # 1-propyl
+        c3_2_path = os.path.join(ARC_PATH, 'arc', 'testing', 'yml_testing', 'C3_2.yml')  # 2-propyl
+        c3_1_spc = ARCSpecies(yml_path=c3_1_path)
+        c3_2_spc = ARCSpecies(yml_path=c3_2_path)
+        rxn_1 = ARCReaction(r_species=[c3_1_spc], p_species=[c3_2_spc])
+        self.assertIsNone(rxn_1.done_opt_r_n_p)
+        rxn_1.check_done_opt_r_n_p()
+        self.assertEqual(rxn_1.done_opt_r_n_p, True)
+
+        rxn_2 = ARCReaction(r_species=[ARCSpecies(label='C1_3', smiles='[CH2]CC')],
+                            p_species=[ARCSpecies(label='C3_2', smiles='C[CH]C')])
+        rxn_2.check_done_opt_r_n_p()
+        self.assertEqual(rxn_2.done_opt_r_n_p, False)
+
+    def tests_white_space_in_reaction_label(self):
+        """Test that an extra white space in the reaction label does not confuse ARC."""
+        hno = ARCSpecies(label='HNO', smiles='N=O')
+        h2no = ARCSpecies(label='H2NO', smiles='N[O]')
+        no = ARCSpecies(label='NO', smiles='[N]=O')
+        nh2oh = ARCSpecies(label='NH2OH', smiles='NO')
+        rxn_1 = ARCReaction(label='HNO + H2NO <=> NO + NH2OH ',
+                            r_species=[hno, h2no], p_species=[no, nh2oh],
+                            )
+        self.assertEqual(rxn_1.reactants, ['H2NO', 'HNO'])
+        self.assertEqual(rxn_1.products, ['NH2OH', 'NO'])
+
+        rxn_2 = ARCReaction(reaction_dict={'label': 'HNO + H2NO <=> NO + NH2OH '},
+                            species_list=[hno, h2no, no, nh2oh],
+                            )
+        self.assertEqual(rxn_2.reactants, ['H2NO', 'HNO'])
+        self.assertEqual(rxn_2.products, ['NH2OH', 'NO'])
+
+    def tests_special_characters_in_reaction_label(self):
+        """Test that the respective species objects can be identified from a reaction label with a special character."""
+        no2 = ARCSpecies(label='NO2', smiles='[O]N=O')
+        nh3o = ARCSpecies(label='[O-][NH3+]', smiles='[O-][NH3+]')
+        hono = ARCSpecies(label='HONO', smiles='ON=O')
+        h2no = ARCSpecies(label='H2NO', smiles='N[O]')
+        rxn_1 = ARCReaction(label='NO2 + [O-][NH3+] <=> HONO + H2NO',
+                            r_species=[no2, nh3o], p_species=[hono, h2no],
+                            )
+        self.assertEqual(rxn_1.reactants, ['NO2', '[O-][NH3p]'])
+        self.assertEqual(rxn_1.products, ['H2NO', 'HONO'])
+
+        rxn_2 = ARCReaction(reaction_dict={'label': 'NO2 + [O-][NH3+] <=> HONO + H2NO'},
+                            species_list=[no2, nh3o, hono, h2no],
+                            )
+        self.assertEqual(rxn_2.reactants, ['NO2', '[O-][NH3p]'])
+        self.assertEqual(rxn_2.products, ['H2NO', 'HONO'])
+
+    def test_get_element_masses(self):
+        """Test the get_element_masses() method."""
+        self.assertTrue(almost_equal_lists(self.rxn1.get_element_mass(),
+                                           [12.0, 1.00782503224, 1.00782503224, 1.00782503224,
+                                            1.00782503224, 15.99491461957, 1.00782503224]))
+        self.assertTrue(almost_equal_lists(self.rxn2.get_element_mass(),
+                                           [12.0, 12.0, 1.00782503224, 1.00782503224, 1.00782503224, 1.00782503224,
+                                            1.00782503224, 15.99491461957, 1.00782503224]))
+        self.assertTrue(almost_equal_lists(self.rxn3.get_element_mass(),
+                                           [12.0, 12.0, 14.00307400443, 1.00782503224, 1.00782503224, 1.00782503224,
+                                            1.00782503224, 1.00782503224, 1.00782503224]))
+        self.assertTrue(almost_equal_lists(self.rxn5.get_element_mass(),
+                                           [14.00307400443, 1.00782503224, 1.00782503224,
+                                            14.00307400443, 1.00782503224, 1.00782503224]))
+
+    def test_get_bonds(self):
+        """Test the get_bonds() method."""
+        r_bonds, p_bonds = self.rxn1.get_bonds()
+        self.assertEqual(r_bonds, [(0, 1), (0, 2), (0, 3), (0, 4), (5, 6)])  # CH4 + OH
+        self.assertEqual(p_bonds, [(0, 1), (0, 2), (0, 3), (4, 5), (4, 6)])  # CH3 + H2O
+
+    def test_multi_reactants(self):
+        """Test that a reaction can be defined with many (>3) reactants or products given ts_xyz_guess."""
+        with self.assertRaises(ReactionError):
+            ARCReaction(r_species=[ARCSpecies(label='C2H6', smiles='CC'),
+                                   ARCSpecies(label='OH', smiles='[OH]'),
+                                   ARCSpecies(label='H2O', smiles='O'),
+                                   ARCSpecies(label='H2O', smiles='O')],
+                        p_species=[ARCSpecies(label='C2H5', smiles='C[CH2]'),
+                                   ARCSpecies(label='H2O', smiles='O'),
+                                   ARCSpecies(label='H2O', smiles='O'),
+                                   ARCSpecies(label='H2O', smiles='O')])
+
+        ARCReaction(r_species=[ARCSpecies(label='C2H6', smiles='CC'),
+                               ARCSpecies(label='OH', smiles='[OH]'),
+                               ARCSpecies(label='H2O', smiles='O'),
+                               ARCSpecies(label='H2O', smiles='O')],
+                    p_species=[ARCSpecies(label='C2H5', smiles='C[CH2]'),
+                               ARCSpecies(label='H2O', smiles='O'),
+                               ARCSpecies(label='H2O', smiles='O'),
+                               ARCSpecies(label='H2O', smiles='O')],
+                    ts_xyz_guess=["""C      -3.61598200   -0.14868700   -0.24629000
+                                    C      -2.87249000   -0.46501800   -1.37357200
+                                    H      -1.49356900   -0.33047800   -1.35181200
+                                    H      -0.84385200    0.11582900   -0.20370300
+                                    H      -1.59912100    0.44823500    0.91958000
+                                    H      -2.97672300    0.31399300    0.89602200
+                                    H      -4.69390100   -0.24965500   -0.26210800
+                                    H      -3.36776700   -0.80869200   -2.27293600
+                                    O      -0.91216500   -0.55783000   -2.23774700
+                                    H      -1.09587000    0.85059200    1.79098900
+                                    O      -3.55685000    0.58245300    1.76982000
+                                    H       0.61957500    0.23804900   -0.17583200
+                                    H       1.21746400   -1.55405900    0.34558600
+                                    O       2.65817800   -1.34488900    0.51012400
+                                    H       3.16323600   -2.29177100    0.72530400
+                                    H       3.06938800   -0.89699200   -0.39503300"""])
+
+    def test_load_ts_xyz_user_guess_from_files(self):
+        """Test various loading a reaction and populating the TS ARCSpecies with user xyz guesses from files"""
+        project_directory = os.path.join(ARC_PATH, 'arc', 'testing', 'reactions', 'methanoate_hydrolysis')
+        input_dict = read_yaml_file(path=os.path.join(project_directory, 'input_1.yml'))
+        input_dict['project_directory'] = project_directory
+        arc_object = ARC(**input_dict)
+        Scheduler(project=arc_object.project,
+                  species_list=arc_object.species,
+                  rxn_list=arc_object.reactions,
+                  conformer_opt_level=arc_object.conformer_opt_level,
+                  opt_level=arc_object.opt_level,
+                  freq_level=arc_object.freq_level,
+                  sp_level=arc_object.sp_level,
+                  scan_level=arc_object.scan_level,
+                  ts_guess_level=arc_object.ts_guess_level,
+                  ess_settings=arc_object.ess_settings,
+                  job_types=arc_object.job_types,
+                  rmg_database=arc_object.rmg_database,
+                  project_directory=arc_object.project_directory,
+                  ts_adapters=arc_object.ts_adapters,
+                  testing=True,
+                  )
+        self.assertEqual(len(arc_object.reactions[0].ts_species.ts_guesses[0].initial_xyz['symbols']), 19)
+        self.assertEqual(len(arc_object.reactions[0].ts_species.ts_guesses[1].initial_xyz['symbols']), 19)
+
+        input_dict = read_yaml_file(path=os.path.join(project_directory, 'input_2.yml'))
+        input_dict['project_directory'] = project_directory
+        arc_object = ARC(**input_dict)
+        Scheduler(project=arc_object.project,
+                  species_list=arc_object.species,
+                  rxn_list=arc_object.reactions,
+                  conformer_opt_level=arc_object.conformer_opt_level,
+                  opt_level=arc_object.opt_level,
+                  freq_level=arc_object.freq_level,
+                  sp_level=arc_object.sp_level,
+                  scan_level=arc_object.scan_level,
+                  ts_guess_level=arc_object.ts_guess_level,
+                  ess_settings=arc_object.ess_settings,
+                  job_types=arc_object.job_types,
+                  rmg_database=arc_object.rmg_database,
+                  project_directory=arc_object.project_directory,
+                  ts_adapters=arc_object.ts_adapters,
+                  testing=True,
+                  )
+        self.assertEqual(len(arc_object.reactions[0].ts_species.ts_guesses), 2)
+        self.assertEqual(len(arc_object.reactions[0].ts_species.ts_guesses[1].initial_xyz['symbols']), 19)
+
+    def test_get_rxn_smiles(self):
+        """Tests the get_rxn_smiles method"""
+        self.assertEqual(self.rxn1.get_rxn_smiles(), "C.[OH]>>[CH3].O")
+        self.assertEqual(self.rxn2.get_rxn_smiles(), "C[CH2].[OH]>>C=C.O")
+        self.assertEqual(self.rxn3.get_rxn_smiles(), "CC[NH]>>[CH2]CN")
+        self.assertEqual(self.rxn4.get_rxn_smiles(), "[NH2].[NH]N>>N.[N]N")
+        self.assertEqual(self.rxn5.get_rxn_smiles(), "[NH2].[NH2]>>[NH].N")
+        self.assertEqual(self.rxn6.get_rxn_smiles(), "[NH2].[NH]N>>N.[N-]=[NH2+]")
+        self.assertEqual(self.rxn7.get_rxn_smiles(), "[NH2].[NH]N>>N.[N]N")
+        self.assertEqual(self.rxn8.get_rxn_smiles(), "C.[OH]>>[CH3].O")
+        self.assertEqual(self.rxn9.get_rxn_smiles(), "NCO[O]>>C=N.[O]O")
+        self.assertEqual(self.rxn10.get_rxn_smiles(), "N=O.[O-][N+]=O>>[O-][NH+]=O.[N]=O")
+        self.assertEqual(self.rxn11.get_rxn_smiles(), "C[CH]C>>[CH2]CC")
+
+    @classmethod
+    def tearDownClass(cls):
+        """A function that is run ONCE after all unit tests in this class."""
+        project_directory = os.path.join(ARC_PATH, 'arc', 'testing', 'reactions', 'methanoate_hydrolysis')
+        sub_folders = ['log_and_restart_archive', 'output']
+        files_to_remove = ['arc.log']
+        for sub_folder in sub_folders:
+            shutil.rmtree(os.path.join(project_directory, sub_folder), ignore_errors=True)
+        for file_path in files_to_remove:
+            full_file_path = os.path.join(project_directory, file_path)
+            if os.path.isfile(full_file_path):
+                os.remove(full_file_path)
+
+
+if __name__ == '__main__':
+    unittest.main(testRunner=unittest.TextTestRunner(verbosity=2))
diff --git a/arc/rmgdb.py b/arc/rmgdb.py
index bb6e9dc6a3..313e463da0 100644
--- a/arc/rmgdb.py
+++ b/arc/rmgdb.py
@@ -160,30 +160,7 @@ def load_rmg_database(rmgdb: RMGDatabase,
     logger.info('\n\n')
 
 
-def determine_family(reaction: 'ARCReaction',
-                     db: Optional[RMGDatabase] = None,
-                     ):
-    """
-    Determine the RMG reaction family for an ARC reaction.
-    A wrapper for ARCReaction.determine_family().
-    This wrapper is useful because it makes a new instance of the rmgdb if needed.
-
-    Args:
-        reaction ('ARCReaction'): An ARCReaction object instance.
-        db (RMGDatabase, optional): The RMG database instance.
-    """
-    global rmg_database_instance
-    if reaction.family is None:
-        db = db or rmg_database_instance
-        if db is None:
-            db = make_rmg_database_object()
-            load_families_only(db)
-        if reaction.rmg_reaction is None:
-            reaction.rmg_reaction_from_arc_species()
-        reaction.determine_family(db)
-
-
-def determine_reaction_family(rmgdb: RMGDatabase,
+def get_reaction_family_products(rmgdb: RMGDatabase,
                               reaction: Reaction,
                               save_order: bool = True,
                               ) -> Tuple[Optional['KineticsFamily'], bool]:
diff --git a/arc/rmgdb_test.py b/arc/rmgdb_test.py
index 5a29777f33..5d92f37bf5 100644
--- a/arc/rmgdb_test.py
+++ b/arc/rmgdb_test.py
@@ -13,8 +13,6 @@
 from rmgpy.species import Species
 
 import arc.rmgdb as rmgdb
-from arc.reaction import ARCReaction
-from arc.species import ARCSpecies
 
 
 class TestRMGDB(unittest.TestCase):
@@ -44,41 +42,6 @@ def test_thermo(self):
         self.assertAlmostEqual(spc.get_entropy(298), 213.71872, 5)
         self.assertAlmostEqual(spc.get_heat_capacity(1000), 54.35016, 5)
 
-    def test_determine_family(self):
-        """Test the determine_family() function."""
-        rxn = ARCReaction(r_species=[ARCSpecies(label='CH2CH2CH3', smiles='[CH2]CC')],
-                          p_species=[ARCSpecies(label='CH3CHCH3', smiles='C[CH]C')])
-        self.assertIsNone(rxn.family)
-        rmgdb.determine_family(rxn, db=None)
-        self.assertEqual(rxn.family.label, 'intra_H_migration')
-
-        rxn = ARCReaction(r_species=[ARCSpecies(label='C2H6', smiles='CC'),
-                                     ARCSpecies(label='OH', smiles='[OH]')],
-                          p_species=[ARCSpecies(label='water', smiles='O'),
-                                     ARCSpecies(label='C2H5', smiles='[CH2]C')])
-        self.assertIsNone(rxn.family)
-        rmgdb.determine_family(rxn, db=self.rmgdb)
-        self.assertEqual(rxn.family.label, 'H_Abstraction')
-
-        r_1 = ARCSpecies(label='C3H6O', smiles='CCC=O')
-        r_2 = ARCSpecies(label='C4H9O', smiles='[CH2]C(C)CO')
-        p_1 = ARCSpecies(label='C3H5O', smiles='CC=C[O]')  # This is the "wrong" resonance structure on purpose.
-        p_2 = ARCSpecies(label='C4H10O', smiles='CC(C)CO')
-        rxn = ARCReaction(reactants=['C3H6O', 'C4H9O'], products=['C3H5O', 'C4H10O'],
-                          r_species=[r_1, r_2], p_species=[p_1, p_2])
-        self.assertIsNone(rxn.family)
-        rmgdb.determine_family(rxn, db=self.rmgdb)
-        self.assertEqual(rxn.family.label, 'H_Abstraction')
-
-        r_1 = ARCSpecies(label='C2H6', smiles='CC')
-        r_2 = ARCSpecies(label='CCOOj', smiles='CCO[O]')
-        p_1 = ARCSpecies(label='CCOOH', smiles='CCOO')
-        p_2 = ARCSpecies(label='C2H5', smiles='C[CH2]')
-        rxn = ARCReaction(r_species=[r_1, r_2], p_species=[p_1, p_2])
-        self.assertIsNone(rxn.family)
-        rmgdb.determine_family(rxn, db=self.rmgdb)
-        self.assertEqual(rxn.family.label, 'H_Abstraction')
-
     def test_determining_rmg_kinetics(self):
         """Test the determine_rmg_kinetics() function"""
         r1 = Species().from_smiles('C')
diff --git a/arc/scheduler.py b/arc/scheduler.py
index b6c7618daf..bb5ce2cd23 100644
--- a/arc/scheduler.py
+++ b/arc/scheduler.py
@@ -14,7 +14,6 @@
 from IPython.display import display
 from typing import TYPE_CHECKING, List, Optional, Tuple, Union
 
-import arc.rmgdb as rmgdb
 from arc import parser, plotter
 from arc.checks.common import get_i_from_job_name, sum_time_delta
 from arc.checks.ts import check_imaginary_frequencies, check_ts, check_irc_species_and_rxn
@@ -145,7 +144,6 @@ class Scheduler(object):
                                           in the species. Keys are tuples of (min_num_atoms, max_num_atoms),
                                           values are dictionaries with job type tuples as keys and levels of theory
                                           as values. 'inf' is accepted in max_num_atoms
-        rmg_database (RMGDatabase, optional): The RMG database object.
         job_types (dict, optional): A dictionary of job types to execute. Keys are job types, values are boolean.
         bath_gas (str, optional): A bath gas. Currently used in OneDMin to calc L-J parameters.
                                   Allowed values are He, Ne, Ar, Kr, H2, N2, O2.
@@ -192,7 +190,6 @@ class Scheduler(object):
         restart_path (str): Path to the `restart.yml` file to be saved.
         max_job_time (float): The maximal allowed job time on the server in hours (can be fractional).
         testing (bool): Used for internal ARC testing (generating the object w/o executing it).
-        rmg_database (RMGDatabase): The RMG database object.
         allow_nonisomorphic_2d (bool): Whether to optimize species even if they do not have a 3D conformer that is
                                        isomorphic to the 2D graph representation.
         dont_gen_confs (list): A list of species labels for which conformer jobs were loaded from a restart file,
@@ -218,7 +215,6 @@ class Scheduler(object):
                                 in the species. Keys are tuples of (min_num_atoms, max_num_atoms),
                                 values are dictionaries with job type tuples as keys and levels of theory
                                 as values. 'inf' is accepted in max_num_atoms
-        rmg_database (RMGDatabase, optional): The RMG database object.
         fine_only (bool): If ``True`` ARC will not run optimization jobs without ``fine=True``.
         kinetics_adapter (str): The statmech software to use for kinetic rate coefficient calculations.
         freq_scale_factor (float): The harmonic frequencies scaling factor.
@@ -244,7 +240,6 @@ def __init__(self,
                  irc_level: Optional[Level] = None,
                  orbitals_level: Optional[Level] = None,
                  adaptive_levels: Optional[dict] = None,
-                 rmg_database: Optional = None,
                  job_types: Optional[dict] = None,
                  rxn_list: Optional[list] = None,
                  bath_gas: Optional[str] = None,
@@ -271,7 +266,6 @@ def __init__(self,
         self.species_list = species_list
         self.project_directory = project_directory
 
-        self.rmg_database = rmg_database or rmgdb.make_rmg_database_object()
         self.restart_dict = restart_dict
         self.rxn_list = rxn_list if rxn_list is not None else list()
         self.max_job_time = max_job_time or default_job_settings.get('job_time_limit_hrs', 120)
@@ -329,8 +323,6 @@ def __init__(self,
 
         if len(self.rxn_list):
             rxn_info_path = self.make_reaction_labels_info_file()
-            logger.info("\nLoading RMG's families...")
-            rmgdb.load_families_only(self.rmg_database)
             for rxn in self.rxn_list:
                 logger.info('\n\n')
                 # 1. Update the ARCReaction object and generate an ARCSpecies object for its TS.
@@ -340,12 +332,10 @@ def __init__(self,
                         rxn.r_species.append(spc)
                     if spc.label in rxn.products:
                         rxn.p_species.append(spc)
-                rxn.rmg_reaction_from_arc_species()
                 rxn.check_attributes()
-                rxn.determine_family(rmg_database=self.rmg_database)
                 family_text = ''
                 if rxn.family is not None:
-                    family_text = f'identified as belonging to RMG family {rxn.family.label}'
+                    family_text = f'identified as belonging to RMG family {rxn.family}'
                 logger.info(f'Considering reaction: {rxn.label}')
                 if family_text:
                     logger.info(f'({family_text})')
@@ -1612,8 +1602,8 @@ def spawn_ts_jobs(self):
                     for method in self.ts_adapters:
                         if method in all_families_ts_adapters or \
                                 (rxn.family is not None
-                                 and rxn.family.label in list(ts_adapters_by_rmg_family.keys())
-                                 and method in ts_adapters_by_rmg_family[rxn.family.label]):
+                                 and rxn.family in list(ts_adapters_by_rmg_family.keys())
+                                 and method in ts_adapters_by_rmg_family[rxn.family]):
                             self.run_job(job_type='tsg',
                                          job_adapter=method,
                                          reactions=[rxn],
@@ -2276,6 +2266,8 @@ def determine_most_likely_ts_conformer(self, label: str):
                     if any(tsg.imaginary_freqs is not None for tsg in self.species_dict[label].ts_guesses) else None,
                 before_optimization=False,
             )
+            if len(self.species_dict[label].ts_guesses) <= 1:
+                self.species_dict[label].ts_guesses_exhausted = True
 
     def parse_composite_geo(self,
                             label: str,
@@ -3818,7 +3810,7 @@ def generate_final_ts_guess_report(self):
                 ts_dict['rxn_index'] = species.rxn_index
                 for reaction in self.rxn_list:
                     if reaction.ts_label == species.label:
-                        ts_dict['family'] = reaction.family.label if reaction.family is not None else None
+                        ts_dict['family'] = reaction.family
                         break
                 else:
                     ts_dict['family'] = None
diff --git a/arc/scheduler_test.py b/arc/scheduler_test.py
index 10d5b1571e..88cb10e396 100644
--- a/arc/scheduler_test.py
+++ b/arc/scheduler_test.py
@@ -9,7 +9,6 @@
 import os
 import shutil
 
-import arc.rmgdb as rmgdb
 import arc.parser as parser
 from arc.checks.ts import check_ts
 from arc.common import ARC_PATH, almost_equal_coords_lists, initialize_job_types, read_yaml_file
@@ -69,7 +68,6 @@ def setUpClass(cls):
                                species=[cls.spc1], xyz=xyz1, job_type='scan', torsions=[[3, 1, 2, 6]], rotor_index=0,
                                level=Level(repr={'method': 'b3lyp', 'basis': 'cbsb7'}),
                                project_directory=cls.project_directory, job_num=104)
-        cls.rmg_database = rmgdb.make_rmg_database_object()
         cls.job_types1 = {'conf_opt': True,
                           'conf_sp': False,
                           'opt': True,
@@ -97,7 +95,6 @@ def setUpClass(cls):
                                sp_level=Level(repr=default_levels_of_theory['sp']),
                                scan_level=Level(repr=default_levels_of_theory['scan']),
                                ts_guess_level=Level(repr=default_levels_of_theory['ts_guesses']),
-                               rmg_database=cls.rmg_database,
                                project_directory=cls.project_directory,
                                testing=True,
                                job_types=cls.job_types1,
@@ -113,7 +110,6 @@ def setUpClass(cls):
                                sp_level=Level(repr=default_levels_of_theory['sp']),
                                scan_level=Level(repr=default_levels_of_theory['scan']),
                                ts_guess_level=Level(repr=default_levels_of_theory['ts_guesses']),
-                               rmg_database=cls.rmg_database,
                                project_directory=cls.project_directory,
                                testing=True,
                                job_types=cls.job_types1,
@@ -128,7 +124,6 @@ def setUpClass(cls):
                                freq_level=Level(repr=default_levels_of_theory['freq_for_composite']),
                                scan_level=Level(repr=default_levels_of_theory['scan_for_composite']),
                                ts_guess_level=Level(repr=default_levels_of_theory['ts_guesses']),
-                               rmg_database=cls.rmg_database,
                                project_directory=cls.project_directory,
                                testing=True,
                                job_types=cls.job_types2,
@@ -229,7 +224,6 @@ def test_determine_adaptive_level(self):
                            sp_level=default_levels_of_theory['sp'],
                            scan_level=default_levels_of_theory['scan'],
                            ts_guess_level=default_levels_of_theory['ts_guesses'],
-                           rmg_database=self.rmg_database,
                            project_directory=self.project_directory,
                            testing=True, job_types=self.job_types1,
                            orbitals_level=default_levels_of_theory['orbitals'],
diff --git a/arc/settings/settings.py b/arc/settings/settings.py
index 72946e303a..bd67079741 100644
--- a/arc/settings/settings.py
+++ b/arc/settings/settings.py
@@ -291,12 +291,16 @@
 # An imaginary frequency is valid if it is between the following range (in cm-1):
 LOWEST_MAJOR_TS_FREQ, HIGHEST_MAJOR_TS_FREQ = 75.0, 10000.0
 
+# ARC families folder path
+ARC_FAMILIES_PATH = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))), 'data', 'families')
+
 # default environment names for sister repos
-TS_GCN_PYTHON, TANI_PYTHON, AUTOTST_PYTHON, ARC_PYTHON, XTB, OB_PYTHON = None, None, None, None, None, None
+TS_GCN_PYTHON, TANI_PYTHON, AUTOTST_PYTHON, ARC_PYTHON, XTB, OB_PYTHON, RMG_DB_PATH = \
+    None, None, None, None, None, None, None
 home = os.getenv("HOME") or os.path.expanduser("~")
 
 tani_pypath_1 = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(sys.executable))),
-                            'tani_env', 'bin', 'python')
+                             'tani_env', 'bin', 'python')
 tani_pypath_2 = os.path.join(home, 'mambaforge', 'envs', 'tani_env', 'bin', 'python')
 tani_pypath_3 = os.path.join(home, 'anaconda3', 'envs', 'tani_env', 'bin', 'python')
 tani_pypath_4 = os.path.join(home, 'miniconda3', 'envs', 'tani_env', 'bin', 'python')
@@ -307,7 +311,7 @@
         TANI_PYTHON = tani_pypath
 
 ob_pypath_1 = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(sys.executable))),
-                            'ob_env', 'bin', 'python')
+                           'ob_env', 'bin', 'python')
 ob_pypath_2 = os.path.join(home, 'mambaforge', 'envs', 'ob_env', 'bin', 'python')
 ob_pypath_3 = os.path.join(home, 'anaconda3', 'envs', 'ob_env', 'bin', 'python')
 ob_pypath_4 = os.path.join(home, 'miniconda3', 'envs', 'ob_env', 'bin', 'python')
@@ -342,7 +346,7 @@
 
 paths = list()
 paths.append(os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(sys.executable))),
-                            'xtb_env', 'bin', 'xtb'))
+                          'xtb_env', 'bin', 'xtb'))
 paths.append(os.path.join(home, 'anaconda3', 'envs', 'xtb_env', 'bin', 'xtb'))
 paths.append(os.path.join(home, 'miniconda3', 'envs', 'xtb_env', 'bin', 'xtb'))
 paths.append(os.path.join(home, '.conda', 'envs', 'xtb_env', 'bin', 'xtb'))
@@ -362,3 +366,20 @@
     if os.path.isfile(arc_pypath):
         ARC_PYTHON = arc_pypath
         break
+
+rmg_db_path_1 = None
+for python_path in sys.path:
+    if 'RMG-database' in python_path:
+        rmg_db_path_1 = python_path
+        break
+rmg_db_path_2 = None
+for python_path in sys.path:
+    if 'RMG-Py' in python_path:
+        rmg_db_path_2 = os.path.join(os.path.dirname(python_path), 'RMG-database')
+        break
+rmg_db_path_3 = os.path.join(home, 'Code', 'RMG-database')
+rmg_db_path_4 = os.path.join(home, 'runner', 'work', 'ARC', 'ARC', 'RMG-database')
+for rmg_db_path in [rmg_db_path_1, rmg_db_path_2, rmg_db_path_3, rmg_db_path_4]:
+    if rmg_db_path is not None and os.path.isdir(rmg_db_path):
+        RMG_DB_PATH = rmg_db_path
+        break
diff --git a/arc/species/species.py b/arc/species/species.py
index 7c0df39d7c..714a1ae666 100644
--- a/arc/species/species.py
+++ b/arc/species/species.py
@@ -1583,11 +1583,6 @@ def mol_from_xyz(self,
         if xyz is None:
             return None
 
-        if len(xyz['symbols']) == 2 and xyz['symbols'][0] == xyz['symbols'][1] \
-                and xyz['symbols'][0] in ['O', 'S'] and self.multiplicity == 3:
-            # Hard-coded for triplet O2 and S2: Don't perceive mol.
-            return None
-
         if self.mol is not None:
             if len(self.mol.atoms) != len(xyz['symbols']):
                 raise SpeciesError(f'The number of atoms in the molecule and in the coordinates of {self.label} is different.'
diff --git a/arc/species/species_test.py b/arc/species/species_test.py
index 7a0b1a5658..04446a36c6 100644
--- a/arc/species/species_test.py
+++ b/arc/species/species_test.py
@@ -1506,6 +1506,14 @@ def test_mol_from_xyz_atom_id_2(self):
         self.assertEqual(mol_ids, res1_ids)
         self.assertEqual(mol_ids, res2_ids)
 
+    def test_perceiving_o2(self):
+        """Test that O2 is correctly perceived"""
+        o2_xyz = {'symbols': ('O', 'O'), 'isotopes': (16, 16), 'coords': ((0.0, 0.0, 0.6029), (0.0, 0.0, -0.6029))}
+        o2 = ARCSpecies(label='O2aa', xyz=o2_xyz, multiplicity=3)
+        self.assertEqual(o2.multiplicity, 3)
+        self.assertEqual(o2.mol.multiplicity, 3)
+        self.assertEqual(o2.mol.to_smiles(), '[O][O]')
+
     def test_preserving_multiplicity(self):
         """Test that multiplicity is being preserved, especially when it is guessed differently from xyz"""
         multiplicity_list = [2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 3, 2, 1]
diff --git a/arc/statmech/arkane_test.py b/arc/statmech/arkane_test.py
index 54e2ec78e7..aae1f39033 100644
--- a/arc/statmech/arkane_test.py
+++ b/arc/statmech/arkane_test.py
@@ -11,7 +11,8 @@
 
 from arc.common import ARC_PATH
 from arc.level import Level
-from arc.reaction import ARCReaction, ARCSpecies
+from arc.reaction import ARCReaction
+from arc.species import ARCSpecies
 from arc.statmech.arkane import ArkaneAdapter
 
 
diff --git a/data/families/ester_hydrolysis/groups.py b/data/families/ester_hydrolysis/groups.py
new file mode 100644
index 0000000000..6301e809fb
--- /dev/null
+++ b/data/families/ester_hydrolysis/groups.py
@@ -0,0 +1,61 @@
+name = "ester_hydrolysis/groups"
+shortDesc = u"ester_hydrolysis"
+longDesc = u"""
+A generic bimolecular ester hydrolysis reaction: R1-A(=C)-B(R2)-R3 + H2O <=> R1-A(=C)-OH + R3-B(R2)-H
+
+Where:
+- A can be C (carbonyl) or P (phosphoryl).
+- B can be O, S, N, or a halide (X).
+- R1, R2, and R3 represent substituent groups or hydrogen depending on the structure of the ester.
+
+R1A(*1)(=C)B(*2)R2 + H(*3)O(*4)H <=> R1A(*1)(=C)O(*4)H + R2B(*2)H(*3)
+
+
+This family encompasses hydrolysis reactions for a range of ester types, including carboxylic, phosphoric, and thioester variants.
+"""
+
+template(reactants=["ester", "H2O"], products=["acid", "alcohol"], ownReverse=False)
+
+#reverse = "condensation"
+
+#reversible = True
+
+recipe(actions=[
+    ['BREAK_BOND', '*1', 1, '*2'],
+    ['BREAK_BOND', '*3', 1, '*4'],
+    ['FORM_BOND', '*1', 1, '*4'],
+    ['FORM_BOND', '*2', 1, '*3'],
+])
+
+entry(
+    index = 0,
+    label = "ester",
+    group = 
+"""
+1    R    u0 {2,S}
+2 *1 [C,P]    u0 {1,S} {3,D} {4,S}
+3    O    u0 {2,D}
+4 *2 O    u0 {2,S}
+""",
+    kinetics = None,
+)
+
+entry(
+    index = 1,
+    label = "H2O",
+    group = 
+"""
+1 *4 O u0 p2 c0 {2,S} {3,S}
+2 *3 H u0 p0 c0 {1,S}
+3    H u0 p0 c0 {1,S}
+""",
+    kinetics = None,
+)
+
+
+tree(
+"""
+L1: ester
+L1: H2O
+"""
+)
diff --git a/data/families/ether_hydrolysis/groups.py b/data/families/ether_hydrolysis/groups.py
new file mode 100644
index 0000000000..4f5e183b5a
--- /dev/null
+++ b/data/families/ether_hydrolysis/groups.py
@@ -0,0 +1,58 @@
+name = "ether_hydrolysis/groups"
+shortDesc = u"ether_hydrolysis"
+longDesc = u"""
+A generic bimolecular ether hydrolysis reaction: R1-A(R2)(R3)-B-R4 + H2O <=> R1-A(R2)(R3)-OH + R4-B-H
+
+Where:
+- A can be C 
+- B can be O
+- R1, R2, and R3 represent substituent groups or hydrogen depending on the structure.
+
+R1-A(*1)(R2)(R3)-B(*2)-R4 + H(*3)O(*4)H <=> R1-A(*1)(R2)(R3)O(*4)H + R4B(*2)H(*3)
+
+"""
+
+template(reactants=["ether", "H2O"], products=["acid", "alcohol"], ownReverse=False)
+
+#reverse = "condensation"
+
+#reversible = True
+
+recipe(actions=[
+    ['BREAK_BOND', '*1', 1, '*2'],
+    ['BREAK_BOND', '*3', 1, '*4'],
+    ['FORM_BOND', '*1', 1, '*4'],
+    ['FORM_BOND', '*2', 1, '*3'],
+])
+
+entry(
+    index = 0,
+    label = "ether",
+    group = 
+"""
+1 *1  C        u0  {2,S} 
+2 *2  O        u0  {1,S} {3,S}
+3     C        u0  {2,S}
+""",
+    kinetics = None,
+)
+
+entry(
+    index = 1,
+    label = "H2O",
+    group = 
+"""
+1 *4 O u0 p2 c0 {2,S} {3,S}
+2 *3 H u0 p0 c0 {1,S}
+3    H u0 p0 c0 {1,S}
+""",
+    kinetics = None,
+)
+
+
+tree(
+"""
+L1: ether
+L1: H2O
+"""
+)
diff --git a/data/families/hydrolysis.py b/data/families/hydrolysis.py
new file mode 100644
index 0000000000..4b6d8f4b3d
--- /dev/null
+++ b/data/families/hydrolysis.py
@@ -0,0 +1,62 @@
+name = "hydrolysis/groups"
+shortDesc = u"hydrolysis"
+longDesc = u"""
+A generic bimolecular hydrolysis reaction: AB + H2O <=> AH + BOH
+
+R1(*1)[O/N](*3)R2(*2) + H(*4)O(*5)H <=> R1(*1)[O/N](*3)H(*4) + R2(*2)O(*5)H
+
+
+
+
+Make sure whether we need a double bond between R1 and O (/N)
+not only C, also P (phosphoesther)
+
+
+
+"""
+
+template(reactants=["R1ONR2", "H2O"], products=["R1ONH", "R2OH"], ownReverse=False)
+
+reverse = "condensation"
+
+reversible = True
+
+recipe(actions=[
+    ['BREAK_BOND', '*3', 1, '*2'],
+    ['BREAK_BOND', '*4', 1, '*5'],
+    ['FORM_BOND', '*3', 1, '*4'],
+    ['FORM_BOND', '*2', 1, '*5'],
+])
+
+entry(
+    index = 0,
+    label = "R1ONR2",
+    group = 
+"""
+1 *1 R!H       u0 p0     c0 {2,S}
+2 *3 [O2s,N3s] u0 p[1,2] c0 {1,S} {3,S}
+3 *2 R!H       u0 p0     c0 {2,S}
+""",
+    kinetics = None,
+)
+
+entry(
+    index = 1,
+    label = "H2O",
+    group = 
+"""
+1 *4 O u0 p2 c0 {2,S} {3,S}
+2 *5 H u0 p0 c0 {1,S}
+3    H u0 p0 c0 {1,S}
+""",
+    kinetics = None,
+)
+
+
+tree(
+"""
+L1: R1ONR2
+L1: H2O
+"""
+)
+
diff --git a/data/families/imine_hydrolysis/groups.py b/data/families/imine_hydrolysis/groups.py
new file mode 100644
index 0000000000..56d3a155ee
--- /dev/null
+++ b/data/families/imine_hydrolysis/groups.py
@@ -0,0 +1,57 @@
+name = "imine_hydrolysis/groups"
+shortDesc = u"imine_hydrolysis"
+longDesc = u"""
+A generic bimolecular imine hydrolysis reaction: R1-A(R2)=N-R3 + H2O <=> R1-A(R2)(OH)-N(H)-R3 
+
+Where:
+- A can be C (carbonyl) or P (phosphoryl).
+- R1,R2, and R3 represent substituent groups or hydrogen depending on the structure of the ester.
+
+R1-A(*1)(R2)=N(*2)-R3 + H(*3)O(*4)H <=> R1-A(*1)(R2)(O(*4)H)-N(*2)(H(*3))-R3
+
+"""
+
+template(reactants=["imine", "H2O"], products=["acid"], ownReverse=False)
+
+#reverse = "condensation"
+
+#reversible = True
+
+recipe(actions=[
+    ['CHANGE_BOND', '*1', -1, '*2'],
+    ['BREAK_BOND', '*3', 1, '*4'],
+    ['FORM_BOND', '*1', 1, '*4'],
+    ['FORM_BOND', '*2', 1, '*3'],
+])
+
+entry(
+    index = 0,
+    label = "imine",
+    group = 
+"""
+1 *1 [C,P]    u0   {2,D}
+2 *2 N     u0   {1,D} {3,S}
+3    R     u0   {2,S}
+""",
+    kinetics = None,
+)
+
+entry(
+    index = 1,
+    label = "H2O",
+    group = 
+"""
+1 *4 O u0 p2 c0 {2,S} {3,S}
+2 *3 H u0 p0 c0 {1,S}
+3    H u0 p0 c0 {1,S}
+""",
+    kinetics = None,
+)
+
+
+tree(
+"""
+L1: imine
+L1: H2O
+"""
+)
diff --git a/data/families/nitrile_hydrolysis/groups.py b/data/families/nitrile_hydrolysis/groups.py
new file mode 100644
index 0000000000..268f215677
--- /dev/null
+++ b/data/families/nitrile_hydrolysis/groups.py
@@ -0,0 +1,57 @@
+name = "nitrile/groups"
+shortDesc = u"nitrile_hydrolysis"
+longDesc = u"""
+A generic bimolecular ester hydrolysis reaction: R1-A#N + H2O <=> R1-A(OH)=NH 
+
+Where:
+- A can be C (carbonyl) or P (phosphoryl).
+- R1 represent substituent groups or hydrogen depending on the structure of the ester.
+
+R1-A(*1)#N(*2) + H(*3)O(*4)H <=> R1-A(O(*4)H)=N(*2)H(*3)
+
+"""
+
+template(reactants=["nitrile", "H2O"], products=["acid"], ownReverse=False)
+
+#reverse = "condensation"
+
+#reversible = True
+
+recipe(actions=[
+    ['CHANGE_BOND', '*1', -1, '*2'],
+    ['BREAK_BOND', '*3', 1, '*4'],
+    ['FORM_BOND', '*1', 1, '*4'],
+    ['FORM_BOND', '*2', 1, '*3'],
+])
+
+entry(
+    index = 0,
+    label = "nitrile",
+    group = 
+"""
+1    R    u0 {2,S}
+2 *1 [C,P]    u0 {1,S} {3,T}
+3 *2 N    u0 {2,T} 
+""",
+    kinetics = None,
+)
+
+entry(
+    index = 1,
+    label = "H2O",
+    group = 
+"""
+1 *4 O u0 p2 c0 {2,S} {3,S}
+2 *3 H u0 p0 c0 {1,S}
+3    H u0 p0 c0 {1,S}
+""",
+    kinetics = None,
+)
+
+
+tree(
+"""
+L1: nitrile
+L1: H2O
+"""
+)
diff --git a/data/families/tests/ester_hydrolysis_test.py b/data/families/tests/ester_hydrolysis_test.py
new file mode 100644
index 0000000000..22e436ba95
--- /dev/null
+++ b/data/families/tests/ester_hydrolysis_test.py
@@ -0,0 +1,117 @@
+import unittest
+from rmgpy.molecule import Molecule
+from arc.reaction.family import ReactionFamily, get_reaction_family_products
+from arc.reaction.reaction import ARCReaction
+from arc.species.species import ARCSpecies
+
+class TestEsterHydrolysisReactionFamily(unittest.TestCase):
+    """
+    Contains unit tests for the ester hydrolysis reaction family.
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """Set up the test by defining the ester hydrolysis reaction family."""
+        cls.family = ReactionFamily('ester_hydrolysis')
+
+    def test_ester_hydrolysis_reaction(self):
+        """Test if ester hydrolysis products are correctly generated."""
+        # Define the ester and water as reactants
+        ester_smiles = 'CC(=O)OC'  # Methyl acetate
+        water_smiles = 'O'
+
+        # Create ARC species for the reactants
+        ester = ARCSpecies(label='ester', smiles=ester_smiles)
+        water = ARCSpecies(label='H2O', smiles=water_smiles)
+
+        # Define the expected products (acetic acid and methanol)
+        acid_smiles = 'CC(=O)O'
+        alcohol_smiles = 'CO'
+
+        acid = ARCSpecies(label='acid', smiles=acid_smiles)
+        alcohol = ARCSpecies(label='alcohol', smiles=alcohol_smiles)
+
+        # Create a reaction instance
+        rxn = ARCReaction(r_species=[ester, water], p_species=[acid, alcohol], rmg_family_set=['ester_hydrolysis'])
+
+        # Get reaction products
+        products = get_reaction_family_products(rxn)
+
+        # Check if the generated products match expected ones
+        product_smiles = [p.molecule[0].to_smiles() for p in products[0]['products']]
+        expected_product_smiles = {acid_smiles, alcohol_smiles}
+
+        self.assertEqual(set(product_smiles), expected_product_smiles)
+    """
+    def test_reverse_reaction(self):
+        # Define the acid and alcohol as reactants for the reverse reaction
+        acid_smiles = 'CC(=O)O'
+        alcohol_smiles = 'CO'
+
+        acid = ARCSpecies(label='acid', smiles=acid_smiles)
+        alcohol = ARCSpecies(label='alcohol', smiles=alcohol_smiles)
+
+        # Define expected ester and water as products
+        ester_smiles = 'CC(=O)OC'
+        water_smiles = 'O'
+
+        ester = ARCSpecies(label='ester', smiles=ester_smiles)
+        water = ARCSpecies(label='H2O', smiles=water_smiles)
+
+        # Create a reaction instance for the reverse reaction
+        rxn_reverse = ARCReaction(r_species=[acid, alcohol], p_species=[ester, water], rmg_family_set=['condensation'])
+
+        # Get reaction products
+        products_reverse = get_reaction_family_products(rxn_reverse)
+
+        # Check if the generated products match expected ones
+        reverse_product_smiles = [p.molecule[0].to_smiles() for p in products_reverse[0]['products']]
+        expected_reverse_product_smiles = {ester_smiles, water_smiles}
+
+        self.assertEqual(set(reverse_product_smiles), expected_reverse_product_smiles)
+    """
+
+    def test_recipe_actions(self):
+        """Test if the reaction recipe is applied correctly."""
+        expected_actions = [
+            ['BREAK_BOND', '*1', 1, '*2'],
+            ['BREAK_BOND', '*3', 1, '*4'],
+            ['FORM_BOND', '*1', 1, '*4'],
+            ['FORM_BOND', '*2', 1, '*3'],
+        ]
+        actions = self.family.recipe.actions  
+        self.assertEqual(actions, expected_actions)
+
+    """def test_reversibility(self):
+        self.assertTrue(self.family.reversible)
+        self.assertEqual(self.family.reverse, "condensation")
+    """
+    
+
+    def test_recognize_hydrolysis_family(self):
+        """Test if the system recognizes a hydrolysis reaction as part of the ester hydrolysis family."""
+        # Define the ester and water as reactants
+        ester_smiles = 'CC(=O)OC'  # Methyl acetate
+        water_smiles = 'O'
+
+        # Define expected products for hydrolysis (acetic acid and methanol)
+        acid_smiles = 'CC(=O)O'
+        alcohol_smiles = 'CO'
+
+        # Create ARC species for reactants and expected products
+        ester = ARCSpecies(label='ester', smiles=ester_smiles)
+        water = ARCSpecies(label='H2O', smiles=water_smiles)
+        acid = ARCSpecies(label='acid', smiles=acid_smiles)
+        alcohol = ARCSpecies(label='alcohol', smiles=alcohol_smiles)
+
+        # Define a reaction with reactants and products
+        rxn = ARCReaction(r_species=[ester, water], p_species=[acid, alcohol])
+
+        # Determine if the system identifies it as a hydrolysis reaction
+        family_detected = rxn.determine_family()  # Should return 'ester_hydrolysis' or similar identifier
+
+        # Assert that the detected family matches ester hydrolysis
+        self.assertEqual(family_detected, 'ester_hydrolysis')
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/ipython/Tools/conformers.ipynb b/ipython/Tools/conformers.ipynb
index ea2cc31476..4097592b6b 100644
--- a/ipython/Tools/conformers.ipynb
+++ b/ipython/Tools/conformers.ipynb
@@ -24,7 +24,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "RDKit WARNING: [13:31:13] Enabling RDKit 2019.09.3 jupyter extensions\n"
+      "/home/leen/mambaforge/envs/arc_env/lib/python3.7/site-packages/paramiko/transport.py:219: CryptographyDeprecationWarning: Blowfish has been deprecated\n",
+      "  \"class\": algorithms.Blowfish,\n"
      ]
     }
    ],
@@ -39,25 +40,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
-    "smiles = 'NCCC(OO)N(C)[CH2]'"
+    "smiles = 'COC(C)C'"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 3,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "Molecule(smiles=\"NCCC(N(C)[CH2])OO\")"
+       "Molecule(smiles=\"COC(C)C\")"
       ]
      },
      "metadata": {},
@@ -68,323 +69,70 @@
      "output_type": "stream",
      "text": [
       "Generating conformers for spc1\n",
-      "Species spc1 has 9 heavy atoms, 2 chiral centers, and 8 torsions. Using 1000 random conformers.\n"
+      "Species spc1 has 5 heavy atoms and 4 torsions. Using 500 random conformers.\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 960x1440 with 8 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Hypothetical number of conformer combinations for spc1: 3.69E+04\n",
-      "Considering diastereomer {(3,): 'S', (6,): 'NS'}\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.09870139    0.41615015   -0.59228004\n",
-      "O       0.61573885    1.66832793   -0.53361063\n",
-      "O       0.08990554    2.49098192   -1.62494385\n",
-      "N      -1.52738522    0.64190965   -0.28592318\n",
-      "C      -1.78195187    1.04489993    1.09437140\n",
-      "C      -2.38491632   -0.49229112   -0.68596473\n",
-      "H      -3.35117237   -0.65734758   -0.21614329\n",
-      "H      -2.11133795   -1.13939867   -1.51553550\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
-      "H       2.62876768    0.06866964   -0.19623259\n",
-      "H       0.68074077   -0.17921973    1.35149876\n",
-      "H       0.06317880   -1.52572764    0.37655780\n",
-      "H      -0.00858755    0.05825311   -1.62743101\n",
-      "H      -0.80726556    2.60233733   -1.25136682\n",
-      "H      -1.28261147    1.98389998    1.35873711\n",
-      "H      -1.42852316    0.27245621    1.78778362\n",
-      "H      -2.85520472    1.15783768    1.28246579\n"
-     ]
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "<Figure size 960x1260 with 7 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Number of conformer combinations for spc1 after reduction: 4.61E+03\n",
-      "Considering diastereomer {(3,): 'R', (6,): 'NS'}\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.35931009    0.62364803    0.17300072\n",
-      "O      -0.74463957    1.19208934   -1.09685450\n",
-      "O      -1.67751431    2.27888173   -0.79217755\n",
-      "N      -1.53837334    0.04256839    0.85245867\n",
-      "C      -1.27345631   -0.32065026    2.24078544\n",
-      "C      -2.17796900   -1.06370425    0.11014096\n",
-      "H      -2.11962146   -1.11856338   -0.97436736\n",
-      "H      -2.78306302   -1.80717477    0.62225778\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
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\n",
-      "text/plain": [
-       "<Figure size 960x1260 with 7 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Number of conformer combinations for spc1 after reduction: 3.46E+03\n",
-      "Lowest force field conformer for spc1 (diastereomer: {(3,): 'R', (6,): 'NS'}):\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.35931009    0.62364803    0.17300072\n",
-      "O      -0.74463957    1.19208934   -1.09685450\n",
-      "O      -1.67751431    2.27888173   -0.79217755\n",
-      "N      -1.53837334    0.04256839    0.85245867\n",
-      "C      -1.27345631   -0.32065026    2.24078544\n",
-      "C      -2.17796900   -1.06370425    0.11014096\n",
-      "H      -2.11962146   -1.11856338   -0.97436736\n",
-      "H      -2.78306302   -1.80717477    0.62225778\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.48914145   -1.16152850   -0.74137459\n",
-      "H       1.12246130   -0.80995322    0.87431868\n",
-      "H       0.01458149    1.45814965    0.78177871\n",
-      "H      -2.39795025    1.70602153   -0.45947225\n",
-      "H      -0.97751270    0.55828902    2.82432722\n",
-      "H      -2.18112490   -0.71397792    2.71370785\n",
-      "H      -0.48967264   -1.07998577    2.33683454\n",
+      "\n",
+      "Hypothetical number of conformer combinations for spc1: 4\n",
+      "Lowest force field conformer for spc1:\n",
+      "C       1.94964781   -0.29400834    0.97178069\n",
+      "O       0.56279091   -0.48244140    1.21761922\n",
+      "C       0.06456902    0.29640535    2.30897469\n",
+      "C      -1.45358356    0.33503686    2.17237164\n",
+      "C       0.45848305   -0.32281872    3.64633932\n",
+      "H       2.55031925   -0.66886328    1.80439917\n",
+      "H       2.17032253    0.76213637    0.78996382\n",
+      "H       2.21670713   -0.86179624    0.07618828\n",
+      "H       0.44655089    1.32215667    2.23942475\n",
+      "H      -1.87725368   -0.67507430    2.20204696\n",
+      "H      -1.73812351    0.76684082    1.20659452\n",
+      "H      -1.91077568    0.93136218    2.96790257\n",
+      "H       1.54225029   -0.28744072    3.79354308\n",
+      "H       0.16706013   -1.37793644    3.69009059\n",
+      "H      -0.01015002    0.20729868    4.48148746\n",
       "\n"
      ]
     },
     {
      "data": {
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+       "<div id=\"3dmolviewer_17306397802163756\"  style=\"position: relative; width: 400px; height: 400px;\">\n",
+       "        <p id=\"3dmolwarning_17306397802163756\" style=\"background-color:#ffcccc;color:black\">You appear to be running in JupyterLab (or JavaScript failed to load for some other reason).  You need to install the 3dmol extension: <br>\n",
        "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
        "        </div>\n",
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-       "  $3Dmolpromise = loadScriptAsync('https://3dmol.csb.pitt.edu/build/3Dmol.js');\n",
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-       "\tviewer_15931963788638885.addModel(\"\\n     RDKit          3D\\n\\n 22 21  0  0  0  0  0  0  0  0999 V2000\\n    3.0964   -0.5827   -0.9299 N   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.0020    0.3606   -0.7067 C   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.8067   -0.3530   -0.0708 C   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.3593    0.6236    0.1730 C   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.7446    1.1921   -1.0969 O   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.6775    2.2789   -0.7922 O   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.5384    0.0426    0.8525 N   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.2735   -0.3207    2.2408 C   0  0  0  0  0  0  0  0  0  0  0  0\\n   -2.1780   -1.0637    0.1101 C   0  0  0  0  0  3  0  0  0  0  0  0\\n   -2.1196   -1.1186   -0.9744 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -2.7831   -1.8072    0.6223 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    3.8711   -0.0941   -1.3789 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.7981   -1.2993   -1.5916 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    1.7219    0.8140   -1.6634 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.3566    1.1605   -0.0479 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.4891   -1.1615   -0.7414 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    1.1225   -0.8100    0.8743 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.0146    1.4581    0.7818 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -2.3980    1.7060   -0.4595 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.9775    0.5583    2.8243 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -2.1811   -0.7140    2.7137 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.4897   -1.0800    2.3368 H   0  0  0  0  0  0  0  0  0  0  0  0\\n  1  2  1  0\\n  1 12  1  0\\n  1 13  1  0\\n  2  3  1  0\\n  2 14  1  0\\n  2 15  1  0\\n  3  4  1  0\\n  3 16  1  0\\n  3 17  1  0\\n  4  7  1  0\\n  4  5  1  0\\n  4 18  1  0\\n  5  6  1  0\\n  6 19  1  0\\n  7  9  1  0\\n  7  8  1  0\\n  8 20  1  0\\n  8 21  1  0\\n  8 22  1  0\\n  9 10  1  0\\n  9 11  1  0\\nM  RAD  1   9   2\\nM  END\\n\",\"sdf\");\n",
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-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Conformer execution time using MMFF94s: 00:01:20\n",
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.35931009    0.62364803    0.17300072\n",
-      "O      -0.74463957    1.19208934   -1.09685450\n",
-      "O      -1.67751431    2.27888173   -0.79217755\n",
-      "N      -1.53837334    0.04256839    0.85245867\n",
-      "C      -1.27345631   -0.32065026    2.24078544\n",
-      "C      -2.17796900   -1.06370425    0.11014096\n",
-      "H      -2.11962146   -1.11856338   -0.97436736\n",
-      "H      -2.78306302   -1.80717477    0.62225778\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.48914145   -1.16152850   -0.74137459\n",
-      "H       1.12246130   -0.80995322    0.87431868\n",
-      "H       0.01458149    1.45814965    0.78177871\n",
-      "H      -2.39795025    1.70602153   -0.45947225\n",
-      "H      -0.97751270    0.55828902    2.82432722\n",
-      "H      -2.18112490   -0.71397792    2.71370785\n",
-      "H      -0.48967264   -1.07998577    2.33683454\n"
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-      "text/html": [
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-       "        <p id=\"3dmolwarning_15931963796348042\" style=\"background-color:#ffcccc;color:black\">You appear to be running in JupyterLab (or JavaScript failed to load for some other reason).  You need to install the 3dmol extension: <br>\n",
-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
-       "        </div>\n",
-       "<script>\n",
+       "    //this is to ignore the existence of requirejs amd\n",
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        "    tag.onload = () => {\n",
-       "      resolve();\n",
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-       "var warn = document.getElementById(\"3dmolwarning_15931963796348042\");\n",
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@@ -418,125 +167,51 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.76618485    1.23898606   -0.98642288\n",
-      "O      -1.66190616    2.33580732   -0.61377362\n",
-      "N      -1.48029137    0.06549927    0.97933758\n",
-      "C      -1.15143989   -0.32953786    2.34512028\n",
-      "C      -2.17747227   -1.01455681    0.25038285\n",
-      "H      -2.17574636   -1.04910535   -0.83652822\n",
-      "H      -2.76925303   -1.75720032    0.77899135\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H       0.09301698    1.45468420    0.85523777\n",
-      "H      -2.37487511    1.76926846   -0.25516720\n",
-      "H      -0.80974875    0.53242452    2.92899176\n",
-      "H      -2.04085344   -0.71607206    2.85674452\n",
-      "H      -0.37799682   -1.10427244    2.38641028\n"
+      "Generated all combinations from scan map\n",
+      "energy: 7.870784875576027\n",
+      "C       1.94964781   -0.29400834    0.97178069\n",
+      "O       0.56279091   -0.48244140    1.21761922\n",
+      "C       0.06456902    0.29640535    2.30897469\n",
+      "C      -1.45358356    0.33503686    2.17237164\n",
+      "C       0.45848305   -0.32281872    3.64633932\n",
+      "H       2.55031925   -0.66886328    1.80439917\n",
+      "H       2.17032253    0.76213637    0.78996382\n",
+      "H       2.21670713   -0.86179624    0.07618828\n",
+      "H       0.44655089    1.32215667    2.23942475\n",
+      "H      -1.87725368   -0.67507430    2.20204696\n",
+      "H      -1.73812351    0.76684082    1.20659452\n",
+      "H      -1.91077568    0.93136218    2.96790257\n",
+      "H       1.54225029   -0.28744072    3.79354308\n",
+      "H       0.16706013   -1.37793644    3.69009059\n",
+      "H      -0.01015002    0.20729868    4.48148746\n"
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     },
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-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.73218711    1.27565290   -0.97968324\n",
-      "O      -2.19573899    1.23297185   -0.99956433\n",
-      "N      -1.50148622    0.05530738    0.93608533\n",
-      "C      -1.20814293   -0.37905727    2.29800937\n",
-      "C      -2.18905918   -0.99907121    0.16182016\n",
-      "H      -2.16172634   -1.00429288   -0.92528513\n",
-      "H      -2.79870249   -1.75094617    0.65595565\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H       0.08451616    1.43469596    0.88690951\n",
-      "H      -2.26919306    0.26173856   -1.09548076\n",
-      "H      -0.87410329    0.46407439    2.91297638\n",
-      "H      -2.11230035   -0.77212313    2.77782506\n",
-      "H      -0.44162705   -1.16079053    2.33646996\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
-       "        </div>\n",
-       "<script>\n",
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       ]
@@ -570,125 +246,51 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.73218711    1.27565290   -0.97968324\n",
-      "O      -2.03761407    1.88389176   -0.71490604\n",
-      "N      -1.50148622    0.05530738    0.93608533\n",
-      "C      -1.20814293   -0.37905727    2.29800937\n",
-      "C      -2.18905918   -0.99907121    0.16182016\n",
-      "H      -2.16172634   -1.00429288   -0.92528513\n",
-      "H      -2.79870249   -1.75094617    0.65595565\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H       0.08451616    1.43469596    0.88690951\n",
-      "H      -2.52410360    1.04137111   -0.60824555\n",
-      "H      -0.87410329    0.46407439    2.91297638\n",
-      "H      -2.11230035   -0.77212313    2.77782506\n",
-      "H      -0.44162705   -1.16079053    2.33646996\n"
+      "Generated all combinations from scan map\n",
+      "energy: 7.870784875627858\n",
+      "C       1.93607978   -0.31080472    0.95417292\n",
+      "O       0.55280632   -0.48183196    1.23097598\n",
+      "C       0.07988396    0.33359775    2.30675635\n",
+      "C      -0.11649938    1.77662822    1.85261164\n",
+      "C      -1.24739113   -0.26015621    2.76581764\n",
+      "H       2.53672217   -0.50957503    1.84687350\n",
+      "H       2.13941957    0.69452421    0.57662631\n",
+      "H       2.21959269   -1.02930252    0.18011196\n",
+      "H       0.78745946    0.29296618    3.14377446\n",
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+       "<div id=\"3dmolviewer_17306397802321062\"  style=\"position: relative; width: 400px; height: 400px;\">\n",
+       "        <p id=\"3dmolwarning_17306397802321062\" style=\"background-color:#ffcccc;color:black\">You appear to be running in JupyterLab (or JavaScript failed to load for some other reason).  You need to install the 3dmol extension: <br>\n",
        "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
        "        </div>\n",
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-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.73218711    1.27565290   -0.97968324\n",
-      "O      -1.56045615    2.42015478   -0.59460290\n",
-      "N      -1.50148622    0.05530738    0.93608533\n",
-      "C      -1.20814293   -0.37905727    2.29800937\n",
-      "C      -2.18905918   -0.99907121    0.16182016\n",
-      "H      -2.16172634   -1.00429288   -0.92528513\n",
-      "H      -2.79870249   -1.75094617    0.65595565\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H       0.08451616    1.43469596    0.88690951\n",
-      "H      -2.30511413    1.89358715   -0.23949646\n",
-      "H      -0.87410329    0.46407439    2.91297638\n",
-      "H      -2.11230035   -0.77212313    2.77782506\n",
-      "H      -0.44162705   -1.16079053    2.33646996\n"
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-      "text/html": [
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-       "        <p id=\"3dmolwarning_1593196379713924\" style=\"background-color:#ffcccc;color:black\">You appear to be running in JupyterLab (or JavaScript failed to load for some other reason).  You need to install the 3dmol extension: <br>\n",
-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
-       "        </div>\n",
-       "<script>\n",
+       "    //this is to ignore the existence of requirejs amd\n",
+       "    var savedexports, savedmodule;\n",
+       "    if (typeof exports !== 'undefined') savedexports = exports;\n",
+       "    else exports = {}\n",
+       "    if (typeof module !== 'undefined') savedmodule = module;\n",
+       "    else module = {}\n",
        "\n",
-       "var loadScriptAsync = function(uri){\n",
-       "  return new Promise((resolve, reject) => {\n",
        "    var tag = document.createElement('script');\n",
        "    tag.src = uri;\n",
        "    tag.async = true;\n",
        "    tag.onload = () => {\n",
-       "      resolve();\n",
+       "        exports = savedexports;\n",
+       "        module = savedmodule;\n",
+       "        resolve();\n",
        "    };\n",
        "  var firstScriptTag = document.getElementsByTagName('script')[0];\n",
        "  firstScriptTag.parentNode.insertBefore(tag, firstScriptTag);\n",
@@ -697,20 +299,21 @@
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        "$3Dmolpromise = null;\n",
-       "  $3Dmolpromise = loadScriptAsync('https://3dmol.csb.pitt.edu/build/3Dmol.js');\n",
+       "  $3Dmolpromise = loadScriptAsync('https://cdnjs.cloudflare.com/ajax/libs/3Dmol/2.0.4/3Dmol-min.js');\n",
        "}\n",
        "\n",
-       "var viewer_1593196379713924 = null;\n",
-       "var warn = document.getElementById(\"3dmolwarning_1593196379713924\");\n",
+       "var viewer_17306397802321062 = null;\n",
+       "var warn = document.getElementById(\"3dmolwarning_17306397802321062\");\n",
        "if(warn) {\n",
        "    warn.parentNode.removeChild(warn);\n",
        "}\n",
        "$3Dmolpromise.then(function() {\n",
-       "viewer_1593196379713924 = $3Dmol.createViewer($(\"#3dmolviewer_1593196379713924\"),{backgroundColor:\"white\"});\n",
-       "\tviewer_1593196379713924.addModel(\"\\n     RDKit          3D\\n\\n 22 21  0  0  0  0  0  0  0  0999 V2000\\n    3.0964   -0.5827   -0.9299 N   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.0020    0.3606   -0.7067 C   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.8067   -0.3530   -0.0708 C   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.3270    0.6390    0.2510 C   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.7322    1.2757   -0.9797 O   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.5605    2.4202   -0.5946 O   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.5015    0.0553    0.9361 N   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.2081   -0.3791    2.2980 C   0  0  0  0  0  0  0  0  0  0  0  0\\n   -2.1891   -0.9991    0.1618 C   0  0  0  0  0  3  0  0  0  0  0  0\\n   -2.1617   -1.0043   -0.9253 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -2.7987   -1.7509    0.6560 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    3.8711   -0.0941   -1.3789 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.7981   -1.2993   -1.5916 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    1.7219    0.8140   -1.6634 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.3566    1.1605   -0.0479 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.4505   -1.1212   -0.7688 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    1.1364   -0.8614    0.8428 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.0845    1.4347    0.8869 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -2.3051    1.8936   -0.2395 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.8741    0.4641    2.9130 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -2.1123   -0.7721    2.7778 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.4416   -1.1608    2.3365 H   0  0  0  0  0  0  0  0  0  0  0  0\\n  1  2  1  0\\n  1 12  1  0\\n  1 13  1  0\\n  2  3  1  0\\n  2 14  1  0\\n  2 15  1  0\\n  3  4  1  0\\n  3 16  1  0\\n  3 17  1  0\\n  4  7  1  0\\n  4  5  1  0\\n  4 18  1  0\\n  5  6  1  0\\n  6 19  1  0\\n  7  9  1  0\\n  7  8  1  0\\n  8 20  1  0\\n  8 21  1  0\\n  8 22  1  0\\n  9 10  1  0\\n  9 11  1  0\\nM  RAD  1   9   2\\nM  END\\n\",\"sdf\");\n",
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-       "\tviewer_1593196379713924.zoomTo();\n",
-       "viewer_1593196379713924.render();\n",
+       "viewer_17306397802321062 = $3Dmol.createViewer(document.getElementById(\"3dmolviewer_17306397802321062\"),{backgroundColor:\"white\"});\n",
+       "viewer_17306397802321062.zoomTo();\n",
+       "\tviewer_17306397802321062.addModel(\"\\n     RDKit          3D\\n\\n 15 14  0  0  0  0  0  0  0  0999 V2000\\n    1.9361   -0.3108    0.9542 C   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.5528   -0.4818    1.2310 O   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.0799    0.3336    2.3068 C   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.1165    1.7766    1.8526 C   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.2474   -0.2602    2.7658 C   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.5367   -0.5096    1.8469 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.1394    0.6945    0.5766 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.2196   -1.0293    0.1801 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.7875    0.2930    3.1438 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.7452    1.8229    0.9567 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.8392    2.2421    1.5930 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.5796    2.3799    2.6398 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.1108   -1.3009    3.0794 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.9772   -0.2714    1.9485 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -1.6677    0.3032    3.6045 H   0  0  0  0  0  0  0  0  0  0  0  0\\n  1  2  1  0\\n  1  6  1  0\\n  1  7  1  0\\n  1  8  1  0\\n  2  3  1  0\\n  3  4  1  0\\n  3  5  1  0\\n  3  9  1  0\\n  4 10  1  0\\n  4 11  1  0\\n  4 12  1  0\\n  5 13  1  0\\n  5 14  1  0\\n  5 15  1  0\\nM  END\\n\",\"sdf\");\n",
+       "\tviewer_17306397802321062.setStyle({\"stick\": {}});\n",
+       "\tviewer_17306397802321062.zoomTo();\n",
+       "viewer_17306397802321062.render();\n",
        "});\n",
        "</script>"
       ]
@@ -722,2937 +325,51 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.73218711    1.27565290   -0.97968324\n",
-      "O      -0.89211930    2.69806968   -0.67089005\n",
-      "N      -1.50148622    0.05530738    0.93608533\n",
-      "C      -1.20814293   -0.37905727    2.29800937\n",
-      "C      -2.18905918   -0.99907121    0.16182016\n",
-      "H      -2.16172634   -1.00429288   -0.92528513\n",
-      "H      -2.79870249   -1.75094617    0.65595565\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H       0.08451616    1.43469596    0.88690951\n",
-      "H      -1.67090270    2.59003608   -0.08803952\n",
-      "H      -0.87410329    0.46407439    2.91297638\n",
-      "H      -2.11230035   -0.77212313    2.77782506\n",
-      "H      -0.44162705   -1.16079053    2.33646996\n"
+      "Generated all combinations from scan map\n",
+      "energy: 9.749572952824904\n",
+      "C       1.97570755   -0.40721326    0.93150548\n",
+      "O       0.57232427   -0.34124102    1.13518725\n",
+      "C       0.13242949    0.33490165    2.31653443\n",
+      "C       0.58847966   -0.36727160    3.59172202\n",
+      "C       0.50535237    1.81410513    2.31226347\n",
+      "H       2.46875381   -0.95799802    1.73633920\n",
+      "H       2.40972960    0.59036332    0.82814888\n",
+      "H       2.15406203   -0.94818218   -0.00237685\n",
+      "H      -0.96200239    0.27491792    2.28537277\n",
+      "H       1.66772981   -0.26606647    3.74524387\n",
+      "H       0.36746398   -1.43852553    3.54105155\n",
+      "H       0.08596810    0.05328315    4.46865938\n",
+      "H       0.22582175    2.27852972    1.36085784\n",
+      "H       1.58290411    1.95985789    2.43966365\n",
+      "H      -0.00139320    2.34562828    3.12410990\n"
      ]
     },
     {
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+       "        <p id=\"3dmolwarning_17306397802353349\" style=\"background-color:#ffcccc;color:black\">You appear to be running in JupyterLab (or JavaScript failed to load for some other reason).  You need to install the 3dmol extension: <br>\n",
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
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-      "C      -2.18905918   -0.99907121    0.16182016\n",
-      "H      -2.16172634   -1.00429288   -0.92528513\n",
-      "H      -2.79870249   -1.75094617    0.65595565\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.73218711    1.27565290   -0.97968324\n",
-      "O      -1.62842084    2.36915522   -0.59860737\n",
-      "N      -1.50148622    0.05530738    0.93608533\n",
-      "C      -1.18822662   -0.45621509    2.26641356\n",
-      "C      -2.23923260   -0.93792867    0.12789613\n",
-      "H      -2.23860714   -0.88850948   -0.95844157\n",
-      "H      -2.85903201   -1.69609543    0.59925868\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H       0.08451616    1.43469596    0.88690951\n",
-      "H      -2.35387297    1.79887226   -0.27243852\n",
-      "H      -0.81400531    0.34446884    2.91410294\n",
-      "H      -2.09184757   -0.84695301    2.74913250\n",
-      "H      -0.44492329   -1.26070457    2.24568833\n"
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.73218711    1.27565290   -0.97968324\n",
-      "O      -1.62842084    2.36915522   -0.59860737\n",
-      "N      -1.50148622    0.05530738    0.93608533\n",
-      "C      -1.20814293   -0.37905727    2.29800937\n",
-      "C      -2.18905918   -0.99907121    0.16182016\n",
-      "H      -2.82414407   -1.73195455    0.65387852\n",
-      "H      -2.01888689   -1.11281645   -0.90553837\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H       0.08451616    1.43469596    0.88690951\n",
-      "H      -2.35387297    1.79887226   -0.27243852\n",
-      "H      -0.87410329    0.46407439    2.91297638\n",
-      "H      -2.11230035   -0.77212313    2.77782506\n",
-      "H      -0.44162705   -1.16079053    2.33646996\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.021\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.09870139    0.41615015   -0.59228004\n",
-      "O       0.61573885    1.66832793   -0.53361063\n",
-      "O       0.08990554    2.49098192   -1.62494385\n",
-      "N      -1.52738522    0.64190965   -0.28592318\n",
-      "C      -1.78195187    1.04489993    1.09437140\n",
-      "C      -2.38491632   -0.49229112   -0.68596473\n",
-      "H      -3.35117237   -0.65734758   -0.21614329\n",
-      "H      -2.11133795   -1.13939867   -1.51553550\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
-      "H       2.62876768    0.06866964   -0.19623259\n",
-      "H       0.68074077   -0.17921973    1.35149876\n",
-      "H       0.06317880   -1.52572764    0.37655780\n",
-      "H      -0.00858755    0.05825311   -1.62743101\n",
-      "H      -0.80726556    2.60233733   -1.25136682\n",
-      "H      -1.28261147    1.98389998    1.35873711\n",
-      "H      -1.42852316    0.27245621    1.78778362\n",
-      "H      -2.85520472    1.15783768    1.28246579\n"
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
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-      "N      -1.53592278    0.62546035   -0.28854213\n",
-      "C      -1.74199476    1.11199211    1.07279533\n",
-      "C      -2.41560851   -0.52143637   -0.59282020\n",
-      "H      -3.36742286   -0.64836854   -0.08334574\n",
-      "H      -2.17467748   -1.21927612   -1.39078818\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
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-      "H      -2.80755939    1.24700520    1.28808486\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.11993484    0.36714106   -0.62648985\n",
-      "O       0.57695808    1.63053108   -0.62505747\n",
-      "O       1.34375906    1.67629067   -1.87172935\n",
-      "N      -1.54932218    0.58531875   -0.31792919\n",
-      "C      -1.79908999    1.04110089    1.04673090\n",
-      "C      -2.39357716   -0.57623449   -0.66409653\n",
-      "H      -3.35376375   -0.73532572   -0.17999089\n",
-      "H      -2.11711029   -1.25300418   -1.46866461\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
-      "H       2.62876768    0.06866964   -0.19623259\n",
-      "H       0.68274014   -0.13689159    1.33359570\n",
-      "H       0.07707355   -1.53082686    0.41976384\n",
-      "H      -0.03261074   -0.03170296   -1.64680661\n",
-      "H       0.57128181    1.72344163   -2.47000313\n",
-      "H      -1.31122283    1.99705710    1.26828115\n",
-      "H      -1.42937677    0.30282123    1.76829651\n",
-      "H      -2.87238203    1.14666840    1.23883975\n"
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.11993484    0.36714106   -0.62648985\n",
-      "O       0.57695808    1.63053108   -0.62505747\n",
-      "O       0.11377493    2.35468732   -1.81052260\n",
-      "N      -1.54932218    0.58531875   -0.31792919\n",
-      "C      -1.79908999    1.04110089    1.04673090\n",
-      "C      -2.39357716   -0.57623449   -0.66409653\n",
-      "H      -3.35376375   -0.73532572   -0.17999089\n",
-      "H      -2.11711029   -1.25300418   -1.46866461\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
-      "H       2.62876768    0.06866964   -0.19623259\n",
-      "H       0.68274014   -0.13689159    1.33359570\n",
-      "H       0.07707355   -1.53082686    0.41976384\n",
-      "H      -0.03261074   -0.03170296   -1.64680661\n",
-      "H      -0.80645843    2.48231593   -1.50432445\n",
-      "H      -1.31122283    1.99705710    1.26828115\n",
-      "H      -1.42937677    0.30282123    1.76829651\n",
-      "H      -2.87238203    1.14666840    1.23883975\n"
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
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-      "C      -2.39357716   -0.57623449   -0.66409653\n",
-      "H      -3.35376375   -0.73532572   -0.17999089\n",
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-      "H      -2.87238203    1.14666840    1.23883975\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.11993484    0.36714106   -0.62648985\n",
-      "O       0.57695808    1.63053108   -0.62505747\n",
-      "O       0.03111043    2.40021105   -1.74483940\n",
-      "N      -1.54932218    0.58531875   -0.31792919\n",
-      "C      -1.78559320    1.25478197    0.95816386\n",
-      "C      -2.35609202   -0.64582739   -0.44124114\n",
-      "H      -3.29836000   -0.75397907    0.08985287\n",
-      "H      -2.07209883   -1.43817150   -1.12922342\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
-      "H       2.62876768    0.06866964   -0.19623259\n",
-      "H       0.68274014   -0.13689159    1.33359570\n",
-      "H       0.07707355   -1.53082686    0.41976384\n",
-      "H      -0.03261074   -0.03170296   -1.64680661\n",
-      "H      -0.86468582    2.51428081   -1.36879021\n",
-      "H      -1.32979683    2.25036159    1.00313126\n",
-      "H      -1.37177346    0.66096925    1.78190006\n",
-      "H      -2.85754659    1.35457004    1.16056048\n"
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-     "name": "stdout",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
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-      "H      -3.35376375   -0.73532572   -0.17999089\n",
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-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
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-      "H      -1.31122283    1.99705710    1.26828115\n",
-      "H      -1.42937677    0.30282123    1.76829651\n",
-      "H      -2.87238203    1.14666840    1.23883975\n"
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.11993484    0.36714106   -0.62648985\n",
-      "O       0.57695808    1.63053108   -0.62505747\n",
-      "O       0.03111043    2.40021105   -1.74483940\n",
-      "N      -1.54932218    0.58531875   -0.31792919\n",
-      "C      -1.79908999    1.04110089    1.04673090\n",
-      "C      -2.39357716   -0.57623449   -0.66409653\n",
-      "H      -3.35376375   -0.73532572   -0.17999089\n",
-      "H      -2.11711029   -1.25300418   -1.46866461\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
-      "H       2.62876768    0.06866964   -0.19623259\n",
-      "H       0.68274014   -0.13689159    1.33359570\n",
-      "H       0.07707355   -1.53082686    0.41976384\n",
-      "H      -0.03261074   -0.03170296   -1.64680661\n",
-      "H      -0.30503394    3.14547346   -1.20774842\n",
-      "H      -1.31122283    1.99705710    1.26828115\n",
-      "H      -1.42937677    0.30282123    1.76829651\n",
-      "H      -2.87238203    1.14666840    1.23883975\n"
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 29.142\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 30.622\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       1.52361433    0.94431669   -2.03814499\n",
-      "C       0.31469728    1.87703111   -1.83464235\n",
-      "O       0.71159780    2.94239692   -0.94492202\n",
-      "O      -0.51586011    3.65799521   -0.59070852\n",
-      "N      -0.26748096    2.43614214   -3.07479159\n",
-      "C      -0.91718866    1.42629358   -3.90403571\n",
-      "C       0.66888971    3.26809904   -3.85902054\n",
-      "H       1.48265772    3.80356872   -3.37567170\n",
-      "H       0.52352548    3.42400409   -4.92471921\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       2.34676013    1.15339116   -0.03449857\n",
-      "H       1.18012877   -0.16606915   -0.20993581\n",
-      "H       2.35554319    1.49693967   -2.49288693\n",
-      "H       1.25981813    0.12404120   -2.71582270\n",
-      "H      -0.46780753    1.31349017   -1.30842344\n",
-      "H      -0.68300587    4.02378029   -1.48298266\n",
-      "H      -1.73893958    0.94569613   -3.36145907\n",
-      "H      -1.36276986    1.88907681   -4.79258149\n",
-      "H      -0.22444890    0.64834326   -4.24320766\n"
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-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 30.643\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       2.85347885    0.43832667   -0.25879422\n",
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-      "O       1.10521108    1.79458445   -3.20222277\n",
-      "N       2.76146579    2.80988199   -1.18885116\n",
-      "C       4.16753039    2.78874511   -1.58249323\n",
-      "C       2.55805742    3.58445486    0.05230400\n",
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-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       1.04660587   -0.64672684    0.24146493\n",
-      "H       1.92050426   -1.31672983   -1.14379813\n",
-      "H       3.83539094    0.19749056   -0.68554187\n",
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-      "H       1.67715106    2.58814978   -3.20603406\n",
-      "H       4.31957466    2.36604523   -2.58207240\n",
-      "H       4.75208129    2.18931335   -0.87440886\n",
-      "H       4.59971635    3.79512600   -1.56202604\n"
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 30.938\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.73218711    1.27565290   -0.97968324\n",
-      "O      -1.62842084    2.36915522   -0.59860737\n",
-      "N      -1.50148622    0.05530738    0.93608533\n",
-      "C      -2.19918102   -0.93636967    0.12407633\n",
-      "C      -2.43272276    1.05698446    1.49590573\n",
-      "H      -2.08066199    2.03807035    1.80589919\n",
-      "H      -3.47564816    0.81266104    1.67965421\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H       0.08451616    1.43469596    0.88690951\n",
-      "H      -2.35387297    1.79887226   -0.27243852\n",
-      "H      -1.53592984   -1.77174512   -0.12668971\n",
-      "H      -3.03940702   -1.36601255    0.68233415\n",
-      "H      -2.59523441   -0.51706216   -0.80729664\n"
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 30.956\n",
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-      "C       2.04469831   -0.85694186   -0.15761569\n",
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-      "C      -1.81869759    0.64848458    1.13301919\n",
-      "H      -2.69816479    1.15825829    1.51810978\n",
-      "H      -1.19262805    0.11695581    1.84526567\n",
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-      "H      -1.61793288    2.64562485   -0.76173186\n",
-      "H      -3.18752976    1.86463647   -0.72872409\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 30.956\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 31.334\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.11993484    0.36714106   -0.62648985\n",
-      "O      -1.52927971    0.28656411   -0.32804294\n",
-      "O      -2.16315511    1.39579872   -1.04363292\n",
-      "N       0.10106918    0.10850562   -2.06531724\n",
-      "C      -0.19359935   -1.26207036   -2.47410865\n",
-      "C       1.43842461    0.53515899   -2.52493839\n",
-      "H       1.89294971    0.09732832   -3.41000212\n",
-      "H       1.96474834    1.35435505   -2.04153163\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
-      "H       2.62876768    0.06866964   -0.19623259\n",
-      "H       0.68274014   -0.13689159    1.33359570\n",
-      "H       0.07707355   -1.53082686    0.41976384\n",
-      "H       0.18468026    1.39826209   -0.39900935\n",
-      "H      -1.99380486    1.05224761   -1.94372677\n",
-      "H      -1.23748182   -1.54153937   -2.29201628\n",
-      "H       0.44125494   -1.96783257   -1.92523582\n",
-      "H       0.02603909   -1.41441499   -3.53644390\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 31.334\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 31.399\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C       1.11324898   -0.76629351    1.38115658\n",
-      "O       1.43097432    0.42518971    2.13185955\n",
-      "O       1.94507864   -0.03106647    3.42481279\n",
-      "N       0.04228871   -1.52869643    2.06034189\n",
-      "C      -0.15191645   -2.86123742    1.49804401\n",
-      "C      -1.23492149   -0.79554839    2.18357100\n",
-      "H      -1.25542094    0.29067345    2.23125885\n",
-      "H      -2.17651811   -1.32484817    2.30352244\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H      -0.05563253    0.32521253   -0.09706466\n",
-      "H       0.55414866   -1.23497311   -0.67078204\n",
-      "H       2.02517868   -1.37880448    1.37754292\n",
-      "H       1.09896924   -0.40311078    3.74663804\n",
-      "H       0.76215476   -3.45898216    1.58643485\n",
-      "H      -0.92882344   -3.40129188    2.05210288\n",
-      "H      -0.44853238   -2.83599546    0.44376012\n"
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 31.518\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
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-      "C      -0.27091258   -1.82582881    0.16341852\n",
-      "O      -0.36017332   -2.11822507   -1.24667122\n",
-      "O      -0.96163369   -3.44922711   -1.35130134\n",
-      "N      -1.62910234   -1.70985929    0.73598378\n",
-      "C      -2.37826841   -0.55155958    0.25691124\n",
-      "C      -1.63723232   -1.78790770    2.21099109\n",
-      "H      -2.45138766   -1.36004562    2.79039742\n",
-      "H      -0.87559729   -2.34653784    2.74915965\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
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-      "H       0.21462271    0.25664885   -0.24623214\n",
-      "H       0.65125205   -0.28014232    1.38661393\n",
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-      "H      -2.52752395   -0.56510973   -0.82867171\n",
-      "H      -1.84899615    0.37503532    0.50928876\n",
-      "H      -3.35873479   -0.48614524    0.74107315\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 32.296\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
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-      "H      -2.63362752   -0.04066357    2.59723062\n"
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 32.303\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -0.73218711    1.27565290   -0.97968324\n",
-      "O      -1.62842084    2.36915522   -0.59860737\n",
-      "N      -1.50148622    0.05530738    0.93608533\n",
-      "C      -2.38691735    1.06487735    1.50734729\n",
-      "C      -1.16577659   -0.99664993    1.91824733\n",
-      "H      -0.27098920   -1.60421263    1.80513084\n",
-      "H      -1.84099504   -1.23801265    2.73493264\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
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-      "H       0.08451616    1.43469596    0.88690951\n",
-      "H      -2.35387297    1.79887226   -0.27243852\n",
-      "H      -2.77715454    1.72797893    0.72718762\n",
-      "H      -3.25845921    0.59032483    1.97365106\n",
-      "H      -1.89263312    1.67878874    2.26822088\n"
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 32.303\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 32.324\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C       0.15277613   -1.33447743   -1.06168428\n",
-      "O       1.14724812   -2.30169845   -1.46124101\n",
-      "O       0.56116109   -3.05625200   -2.57090401\n",
-      "N      -1.05865364   -2.02228533   -0.56282058\n",
-      "C      -2.19109525   -1.12002953   -0.38096759\n",
-      "C      -0.82796969   -2.85856067    0.63358479\n",
-      "H       0.14415296   -3.30663094    0.82537333\n",
-      "H      -1.64136746   -3.10626376    1.31047329\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       1.15783441   -0.89122575    0.81879259\n",
-      "H       0.07646980    0.39468800    0.26000786\n",
-      "H      -0.11492230   -0.77690336   -1.96956490\n",
-      "H      -0.13045262   -3.50037752   -2.03957306\n",
-      "H      -2.46836747   -0.64595996   -1.32913215\n",
-      "H      -3.07385191   -1.67635629   -0.04412081\n",
-      "H      -1.99056427   -0.33288532    0.35409977\n"
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-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 32.488\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
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-      "N      -0.92323762    1.31836088   -0.92050213\n",
-      "C      -1.67441802    0.41173189   -1.78265751\n",
-      "C       0.03218035    2.14065990   -1.69183745\n",
-      "H       0.90014001    2.58832880   -1.21349569\n",
-      "H      -0.14820621    2.37859251   -2.73682528\n",
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-      "H      -2.12582618    0.96221243   -2.61657979\n",
-      "H      -1.05073252   -0.38378575   -2.20491429\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 33.138\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 33.138\n",
-      "N       3.09635093   -0.58272179   -0.92994681\n",
-      "C       2.00200210    0.36058082   -0.70670001\n",
-      "C       0.80670485   -0.35299868   -0.07076216\n",
-      "C      -0.32697349    0.63901000    0.25101751\n",
-      "O      -1.26203087   -0.01574292    1.13481779\n",
-      "O      -2.42966516    0.86387654    1.21908409\n",
-      "N       0.10813967    1.92888441    0.83102384\n",
-      "C       0.85067562    2.75626816   -0.11429966\n",
-      "C       0.81761162    1.80144118    2.12112659\n",
-      "H       0.61853132    0.96775658    2.79038684\n",
-      "H       1.49969184    2.57442581    2.46523724\n",
-      "H       3.87109150   -0.09412127   -1.37893052\n",
-      "H       2.79806365   -1.29928434   -1.59162866\n",
-      "H       1.72191012    0.81398608   -1.66337825\n",
-      "H       2.35661963    1.16045024   -0.04786320\n",
-      "H       0.45047932   -1.12120446   -0.76879602\n",
-      "H       1.13637636   -0.86136482    0.84278475\n",
-      "H      -0.87578459    0.84489151   -0.67807758\n",
-      "H      -1.97897572    1.58760448    1.69969461\n",
-      "H       0.23557061    2.99770723   -0.98836538\n",
-      "H       1.12260308    3.71361112    0.34588990\n",
-      "H       1.77285406    2.27750575   -0.46143964\n"
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-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 33.256\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.11993484    0.36714106   -0.62648985\n",
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-      "C      -2.13420899    1.70860201   -1.07815702\n",
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
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-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Changing dihedrals on most stable conformer, iteration 0\n",
-      "energy: 33.952\n",
-      "N       2.71387389   -1.80616462    0.73002753\n",
-      "C       2.04469831   -0.85694186   -0.15761569\n",
-      "C       0.62118188   -0.58236863    0.33258236\n",
-      "C      -0.11993484    0.36714106   -0.62648985\n",
-      "O      -0.19723540   -0.27696071   -1.91527753\n",
-      "O      -1.14394165    0.50884872   -2.70932997\n",
-      "N       0.48198125    1.70940901   -0.77472310\n",
-      "C       1.88975135    1.68909319   -1.16226547\n",
-      "C       0.25697233    2.57111755    0.40367990\n",
-      "H       0.91697235    3.40707808    0.62092752\n",
-      "H      -0.61931436    2.44435862    1.03442135\n",
-      "H       2.80244708   -1.39817382    1.66053688\n",
-      "H       3.66722215   -1.95648617    0.39982032\n",
-      "H       2.01952332   -1.27891039   -1.16803788\n",
-      "H       2.62876768    0.06866964   -0.19623259\n",
-      "H       0.68274014   -0.13689159    1.33359570\n",
-      "H       0.07707355   -1.53082686    0.41976384\n",
-      "H      -1.15522455    0.47786168   -0.27483022\n",
-      "H      -0.58917518    1.31208949   -2.77189399\n",
-      "H       2.05487320    1.19533693   -2.12657388\n",
-      "H       2.48418772    1.15783294   -0.40939788\n",
-      "H       2.30012630    2.70328928   -1.21708149\n"
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-       "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
-       "        </div>\n",
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        "    tag.onload = () => {\n",
-       "      resolve();\n",
+       "        exports = savedexports;\n",
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+       "        resolve();\n",
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        "$3Dmolpromise = null;\n",
-       "  $3Dmolpromise = loadScriptAsync('https://3dmol.csb.pitt.edu/build/3Dmol.js');\n",
+       "  $3Dmolpromise = loadScriptAsync('https://cdnjs.cloudflare.com/ajax/libs/3Dmol/2.0.4/3Dmol-min.js');\n",
        "}\n",
        "\n",
-       "var viewer_15931963805797093 = null;\n",
-       "var warn = document.getElementById(\"3dmolwarning_15931963805797093\");\n",
+       "var viewer_17306397802353349 = null;\n",
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-       "\tviewer_15931963805797093.zoomTo();\n",
-       "viewer_15931963805797093.render();\n",
+       "viewer_17306397802353349 = $3Dmol.createViewer(document.getElementById(\"3dmolviewer_17306397802353349\"),{backgroundColor:\"white\"});\n",
+       "viewer_17306397802353349.zoomTo();\n",
+       "\tviewer_17306397802353349.addModel(\"\\n     RDKit          3D\\n\\n 15 14  0  0  0  0  0  0  0  0999 V2000\\n    1.9757   -0.4072    0.9315 C   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.5723   -0.3412    1.1352 O   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.1324    0.3349    2.3165 C   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.5885   -0.3673    3.5917 C   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.5054    1.8141    2.3123 C   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.4688   -0.9580    1.7363 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.4097    0.5904    0.8281 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    2.1541   -0.9482   -0.0024 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.9620    0.2749    2.2854 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    1.6677   -0.2661    3.7452 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.3675   -1.4385    3.5411 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.0860    0.0533    4.4687 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    0.2258    2.2785    1.3609 H   0  0  0  0  0  0  0  0  0  0  0  0\\n    1.5829    1.9599    2.4397 H   0  0  0  0  0  0  0  0  0  0  0  0\\n   -0.0014    2.3456    3.1241 H   0  0  0  0  0  0  0  0  0  0  0  0\\n  1  2  1  0\\n  1  6  1  0\\n  1  7  1  0\\n  1  8  1  0\\n  2  3  1  0\\n  3  4  1  0\\n  3  5  1  0\\n  3  9  1  0\\n  4 10  1  0\\n  4 11  1  0\\n  4 12  1  0\\n  5 13  1  0\\n  5 14  1  0\\n  5 15  1  0\\nM  END\\n\",\"sdf\");\n",
+       "\tviewer_17306397802353349.setStyle({\"stick\": {}});\n",
+       "\tviewer_17306397802353349.zoomTo();\n",
+       "viewer_17306397802353349.render();\n",
        "});\n",
        "</script>"
       ]
@@ -3717,7 +435,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -3731,7 +449,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.16"
   },
   "pycharm": {
    "stem_cell": {
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diff --git a/test_families.py b/test_families.py
new file mode 100644
index 0000000000..a17dd783c7
--- /dev/null
+++ b/test_families.py
@@ -0,0 +1,282 @@
+import unittest
+import sys
+import os
+
+# Add the path to the directory where ester_hydrolysis is located
+sys.path.append('/home/leen/Code/ARC/data/families')
+
+
+from arc.reaction.family import ReactionFamily, get_reaction_family_products, get_recipe_actions
+from arc.reaction.reaction import ARCReaction
+from arc.species.species import ARCSpecies
+
+# Print the current working directory to confirm the script's execution location
+print("Current working directory:", os.getcwd())
+
+class TestEsterHydrolysisReactionFamily(unittest.TestCase):
+    """
+    Contains unit tests for the ester hydrolysis reaction family.
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """Set up the test by defining the ester hydrolysis reaction family."""
+        cls.family = ReactionFamily('ester_hydrolysis')
+
+    def test_ester_hydrolysis_reaction(self):
+        """Test if ester hydrolysis products are correctly generated."""
+        # Define the ester and water as reactants
+        ester_smiles = 'CC(=O)OC'  # Methyl acetate
+        water_smiles = 'O'
+
+        # Create ARC species for the reactants
+        ester = ARCSpecies(label='ester', smiles=ester_smiles)
+        water = ARCSpecies(label='H2O', smiles=water_smiles)
+
+        # Define the expected products (acetic acid and methanol)
+        acid_smiles = 'CC(=O)O'
+        alcohol_smiles = 'CO'
+
+        acid = ARCSpecies(label='acid', smiles=acid_smiles)
+        alcohol = ARCSpecies(label='alcohol', smiles=alcohol_smiles)
+
+        # Create a reaction instance
+        rxn = ARCReaction(r_species=[ester, water], p_species=[acid, alcohol], rmg_family_set=['ester_hydrolysis'])
+
+        # Get reaction products
+        products = get_reaction_family_products(rxn)
+
+        # Check if the generated products match expected ones
+        product_smiles = [p.to_smiles() for p in products[0]['products']]
+        expected_product_smiles = {acid_smiles, alcohol_smiles}
+
+        self.assertEqual(set(product_smiles), expected_product_smiles)
+
+    def test_recipe_actions(self):
+        """Test if the reaction recipe is applied correctly."""
+        # Load the groups.py file content as lines
+        groups_file_path = '/home/leen/Code/ARC/data/families/ester_hydrolysis/groups.py'
+        with open(groups_file_path, 'r') as f:
+            groups_as_lines = f.readlines()
+
+        # Get the recipe actions from the groups file content
+        actions = get_recipe_actions(groups_as_lines)
+
+        # Define the expected actions
+        expected_actions = [
+            ['BREAK_BOND', '*1', 1, '*2'],
+            ['BREAK_BOND', '*3', 1, '*4'],
+            ['FORM_BOND', '*1', 1, '*4'],
+            ['FORM_BOND', '*2', 1, '*3'],
+        ]
+
+        # Assert that the actions match the expected actions
+        self.assertEqual(actions, expected_actions)
+
+    def test_ester_hydrolysis_withP(self):
+        """Test if ester hydrolysis products are correctly generated."""
+        # Define the ester and water as reactants
+        ester_smiles = 'CP(=O)(OC)O'  # Phosphoester
+        water_smiles = 'O'
+
+        # Create ARC species for the reactants
+        ester = ARCSpecies(label='ester', smiles=ester_smiles)
+        water = ARCSpecies(label='H2O', smiles=water_smiles)
+
+        # Define the expected products (acetic acid and methanol)
+        acid_smiles = 'CP(=O)(O)O'
+        alcohol_smiles = 'CO'
+
+        acid = ARCSpecies(label='acid', smiles=acid_smiles)
+        alcohol = ARCSpecies(label='alcohol', smiles=alcohol_smiles)
+
+        # Create a reaction instance
+        rxn = ARCReaction(r_species=[ester, water], p_species=[acid, alcohol], rmg_family_set=['ester_hydrolysis'])
+
+        # Get reaction products
+        products = get_reaction_family_products(rxn)
+
+        # Check if the generated products match expected ones
+        product_smiles = [p.to_smiles() for p in products[0]['products']]
+        expected_product_smiles = {acid_smiles, alcohol_smiles}
+
+        self.assertEqual(set(product_smiles), expected_product_smiles)
+
+
+class TestNitrileHydrolysisReactionFamily(unittest.TestCase):
+    """
+    Contains unit tests for the nitrile hydrolysis reaction family.
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """Set up the test by defining the nitrile hydrolysis reaction family."""
+        cls.family = ReactionFamily('nitrile_hydrolysis')
+
+    def test_nitrile_hydrolysis_reaction(self):
+        """Test if nitrile hydrolysis products are correctly generated."""
+        # Define the nitrile and water as reactants
+        nitrile_smiles = 'CC#N'  # Acetonitrile
+        water_smiles = 'O'
+
+        # Create ARC species for the reactants
+        nitrile = ARCSpecies(label='nitrile', smiles=nitrile_smiles)
+        water = ARCSpecies(label='H2O', smiles=water_smiles)
+
+        # Define the expected products (acetamide as an intermediate and methanol)
+        acid_smiles = 'CC(=N)O'  # Acetamide
+        acid = ARCSpecies(label='acid', smiles=acid_smiles)
+
+        # Create a reaction instance
+        rxn = ARCReaction(r_species=[nitrile, water], p_species=[acid], rmg_family_set=['nitrile_hydrolysis'])
+
+        # Get reaction products
+        products = get_reaction_family_products(rxn)
+
+        # Check if the generated products match expected ones
+        product_smiles = [p.to_smiles() for p in products[0]['products']]
+        expected_product_smiles = {acid_smiles}
+
+        self.assertEqual(set(product_smiles), expected_product_smiles)
+
+    def test_recipe_actions(self):
+        """Test if the reaction recipe is applied correctly for nitrile hydrolysis."""
+        # Load the groups.py file content as lines
+        groups_file_path = '/home/leen/Code/ARC/data/families/nitrile_hydrolysis/groups.py'
+        with open(groups_file_path, 'r') as f:
+            groups_as_lines = f.readlines()
+
+        # Get the recipe actions from the groups file content
+        actions = get_recipe_actions(groups_as_lines)
+
+        # Define the expected actions for nitrile hydrolysis
+        expected_actions =[
+        ['CHANGE_BOND', '*1', -1, '*2'],
+        ['BREAK_BOND', '*3', 1, '*4'],
+        ['FORM_BOND', '*1', 1, '*4'],
+        ['FORM_BOND', '*2', 1, '*3'],
+        ]
+
+        # Assert that the actions match the expected actions
+        self.assertEqual(actions, expected_actions)
+
+class TestImineHydrolysisReactionFamily(unittest.TestCase):
+    """
+    Contains unit tests for the imine hydrolysis reaction family.
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """Set up the test by defining the imine hydrolysis reaction family."""
+        cls.family = ReactionFamily('imine_hydrolysis')
+
+    def test_imine_hydrolysis_reaction(self):
+        """Test if imine hydrolysis products are correctly generated."""
+        # Define the imine and water as reactants
+        imine_smiles = 'CC(=N)C'  
+        water_smiles = 'O'
+
+        # Create ARC species for the reactants
+        imine = ARCSpecies(label='imine', smiles=imine_smiles)
+        water = ARCSpecies(label='H2O', smiles=water_smiles)
+
+        # Define the expected product (assuming a hydrolyzed imine product)
+        acid_smiles = 'CC(O)(N)C'  # Example hydrolyzed product
+        acid = ARCSpecies(label='acid', smiles=acid_smiles)
+
+        # Create a reaction instance
+        rxn = ARCReaction(r_species=[imine, water], p_species=[acid], rmg_family_set=['imine_hydrolysis'])
+
+        # Get reaction products
+        products = get_reaction_family_products(rxn)
+
+        # Check if the generated products match expected ones
+        product_smiles = [p.to_smiles() for p in products[0]['products']]
+        expected_product_smiles = {acid_smiles}
+
+        self.assertEqual(set(product_smiles), expected_product_smiles)
+
+    def test_recipe_actions(self):
+        """Test if the reaction recipe is applied correctly for imine hydrolysis."""
+        # Load the groups.py file content as lines
+        groups_file_path = '/home/leen/Code/ARC/data/families/imine_hydrolysis/groups.py'
+        with open(groups_file_path, 'r') as f:
+            groups_as_lines = f.readlines()
+
+        # Get the recipe actions from the groups file content
+        actions = get_recipe_actions(groups_as_lines)
+
+        # Define the expected actions for imine hydrolysis
+        expected_actions = [
+            ['CHANGE_BOND', '*1', -1, '*2'],
+            ['BREAK_BOND', '*3', 1, '*4'],
+            ['FORM_BOND', '*1', 1, '*4'],
+            ['FORM_BOND', '*2', 1, '*3'],
+        ]
+
+        # Assert that the actions match the expected actions
+        self.assertEqual(actions, expected_actions)
+
+class TestEtherHydrolysisReactionFamily(unittest.TestCase):
+    """
+    Contains unit tests for the ether hydrolysis reaction family.
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """Set up the test by defining the ester hydrolysis reaction family."""
+        cls.family = ReactionFamily('ether_hydrolysis')
+
+    def test_ether_hydrolysis_reaction(self):
+        """Test if ether hydrolysis products are correctly generated."""
+        # Define the ether and water as reactants
+        ether_smiles = 'CCOC'  # Dimethyl ether
+        water_smiles = 'O'
+
+        # Create ARC species for the reactants
+        ether = ARCSpecies(label='ether', smiles=ether_smiles)
+        water = ARCSpecies(label='H2O', smiles=water_smiles)
+
+        # Define the expected products 
+        acid_smiles = 'CCO'
+        alcohol_smiles = 'CO'
+
+        acid = ARCSpecies(label='acid', smiles=acid_smiles)
+        alcohol = ARCSpecies(label='alcohol', smiles=alcohol_smiles)
+
+        # Create a reaction instance
+        rxn = ARCReaction(r_species=[ether, water], p_species=[acid, alcohol], rmg_family_set=['ether_hydrolysis'])
+
+        # Get reaction products
+        products = get_reaction_family_products(rxn)
+
+        # Check if the generated products match expected ones
+        product_smiles = [p.to_smiles() for p in products[0]['products']]
+        expected_product_smiles = {acid_smiles, alcohol_smiles}
+
+        self.assertEqual(set(product_smiles), expected_product_smiles)
+
+    def test_recipe_actions(self):
+        """Test if the reaction recipe is applied correctly."""
+        # Load the groups.py file content as lines
+        groups_file_path = '/home/leen/Code/ARC/data/families/ether_hydrolysis/groups.py'
+        with open(groups_file_path, 'r') as f:
+            groups_as_lines = f.readlines()
+
+        # Get the recipe actions from the groups file content
+        actions = get_recipe_actions(groups_as_lines)
+
+        # Define the expected actions
+        expected_actions = [
+        ['BREAK_BOND', '*1', 1, '*2'],
+        ['BREAK_BOND', '*3', 1, '*4'],
+        ['FORM_BOND', '*1', 1, '*4'],
+        ['FORM_BOND', '*2', 1, '*3'],
+        ]
+
+        # Assert that the actions match the expected actions
+        self.assertEqual(actions, expected_actions)
+
+
+if __name__ == '__main__':
+    unittest.main()