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updated JOSS paper
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CalystaT committed Aug 29, 2023
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title: 'MacroDensity: Understanding The Electrostatic Potential and Density Landscapes within Systems from Quantum Mechanical Sumulations'
title: 'MacroDensity: Understanding The Electrostatic Potential and Electron Density Landscapes within Systems of Quantum Mechanical Simulations'
tags:
- Python
- Density Functional Theory
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MacroDensity is a set of Python modules developed to read and analyse electrostatic potentials and electron
density data from electronic structure calculations derived from Density Functional Theory (DFT). The package
allows users to read from VASP LOCPOT, CHGCAR files, FHI-AIMS *.cube file, and GULP *.out
allows users to read from VASP LOCPOT [@vasp], CHGCAR files, FHI-AIMS [@fhi_aims] , *.cube file, and GULP *.out
file and format the data into physically meaningful quantities, which can then be plotted for user interpretation.
The code has been used to rapidly generate data for these publications: 1,2, amongst others.

The package reads the electron density values from each grid point and averages it along a user defined vector
or plane.
(MOVE ME TO ANOTHER SECTION)
#The code has been used to rapidly generate data for these publications: 1,2, amongst others.#

The package formats datasets containing information about a system's lattice parameters electron density, and
electrostatic potentials. ``MacroDensity`` contains some high-level tools and functions to calculate
the planar and macroscopic average (as defined in Jackson's Electrodynamics [@Jackson:1999]), the spherical average
around a user-defined point, and calculates band energy offsets, deformation potential, and volume changes of a system.
``MacroDensity`` can also calculate the localised potential around a certain atomic nucleus of a system. The approach
to calculating this on site (Hartree) potential is similar to calculating the Madelung potential. this is useful for
electron energy level predictions [@aron:2014].

# Citations

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