diff --git a/book/pages/scattering_parameters.ipynb b/book/pages/scattering_parameters.ipynb
index 7ae9760..a51a69d 100644
--- a/book/pages/scattering_parameters.ipynb
+++ b/book/pages/scattering_parameters.ipynb
@@ -42,14 +42,6 @@
     "S-Parameters are used in circuit-level simulation software, e.g. simphony, sax, Lumerical Interconnect, etc."
    ]
   },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## TODO: Demonstration of using simphony to simulate a circuit quickly using s-parameters\n"
-   ]
-  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -57,7 +49,9 @@
    "source": [
     "## How to find S-Parameters for an arbitrary device using a meep simulation\n",
     "\n",
-    "In this section we'll demonstrate how to find the s-params for any device using a meep simulation. We'll show both 2D and 3D simulations, but keep in mind that 2D s-params are not very accurate. We'll run through the steps using gdsfactory's default 2x2 mmi, and explain on the way how the principles can be applied to any component. There are other ways to find s-parameters, and another method is shown on the [Gds To Meep](/pages/gds_to_meep) page"
+    "In this section we'll demonstrate how to find the s-params for any device using a meep simulation. We'll show both 2D and 3D simulations, but keep in mind that 2D s-params are not very accurate, but the simulations run much faster. It is often recommended to set up the simulation in 2D to ensure everything works, then extend the simulation into 3D to run the final simulations. This can save us a lot of debugging time since the 2D simulations run faster.\n",
+    "\n",
+    "We'll run through the steps using gdsfactory's default 2x2 mmi, and explain on the way how the principles can be applied to any component. There are other ways to find s-parameters, and another method is shown on the [Gds To Meep](/pages/gds_to_meep) page"
    ]
   },
   {
@@ -67,7 +61,7 @@
    "source": [
     "### Step 1 - Import Geometry\n",
     "\n",
-    "For our simulation, it makes life easy if we add all of our sources and detectors into our gds before we import it into meep. For this tutorial I have already done this. For your simulations, you can modify your gds file directly in Klayout if you like a GUI, or you can use gdsfactory itself. If you like, you can also use meep to do the same thing, but I won't be showing how to do that here. This tutorial is adapted from the [GDSII Import](https://meep.readthedocs.io/en/latest/Python_Tutorials/GDSII_Import/) tutorial on the meep documentation\n",
+    "If we have a gds of the device t can make life easy if we add all of our sources and detectors into our gds before we import it into meep. For this tutorial I have already done this. For your simulations, you can modify your gds file directly in Klayout if you like a GUI, or you can use gdsfactory itself. If you like, you can also use meep to do the same thing, but I won't be showing how to do that here. This tutorial is adapted from the [GDSII Import](https://meep.readthedocs.io/en/latest/Python_Tutorials/GDSII_Import/) tutorial on the meep documentation\n",
     "\n",
     "Here is a picture of the gds we will be using. \n",
     "\n",
@@ -684,23 +678,10 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31mFailed to start the Kernel. \n",
-      "\u001b[1;31mKernel Python 3.9.6 is not usable. Check the Jupyter output tab for more information. \n",
-      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
-     ]
-    }
-   ],
    "source": [
-    "\n"
+    "## Import the generated s-matrix to be used in simphony"
    ]
   },
   {