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@andyfaff
Last active August 14, 2024 06:06
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Volume fraction profile generator
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "126199f1",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from refnx.reflect import SLD, Structure, Slab, sld_profile\n",
"%matplotlib inline\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "845a4d42",
"metadata": {},
"outputs": [],
"source": [
"si = SLD(0)\n",
"d2o = SLD(6.36)\n",
"sio2 = SLD(3.47)\n",
"polymer = SLD(1.0)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "acd1fa74",
"metadata": {},
"outputs": [],
"source": [
"s = si | sio2(13, 3) | polymer(25, 3, 0.3) | d2o(0, 4)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "f40ad291",
"metadata": {},
"outputs": [],
"source": [
"slabs = s.slabs()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "96dffe54",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 0. , 0. , 0. , 0. , 0. ],\n",
" [13. , 3.47 , 0. , 3. , 0. ],\n",
" [25. , 2.608, 0. , 3. , 0.3 ],\n",
" [ 0. , 6.36 , 0. , 4. , 0. ]])"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"slabs"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "5aee81c9",
"metadata": {},
"outputs": [],
"source": [
"from refnx.reflect.structure import sld_profile\n",
"def create_vfp(structure, solvent_slab=-1):\n",
" \"\"\"\n",
" Creates a volume fraction profile for a given Structure\n",
" \n",
" Parameters\n",
" ----------\n",
" structure: Structure\n",
" \n",
" solvent_slab: {int, None}\n",
" Defines which slab in `structure` is specified to contain\n",
" the solvent. Use -1 if solvation is done by the backing medium\n",
" If solvation is done by fronting medium use 0.\n",
" If None, then solvation is done by neither fronting or backing,\n",
" but by another material. This might be a solvent vapour in an\n",
" air-solid measurement.\n",
" \n",
" Returns\n",
" -------\n",
" z, vfp: np.ndarray\n",
" z is the distance through the interface, Angstrom\n",
"\n",
" vfp is the array containing the volume fraction profiles for\n",
" each of the slabs from the structure.\n",
" \n",
" In the case where `solvent_slab is None` then\n",
" `vfp.shape == (len(structure.slabs()) + 1, len(z))` and the last\n",
" row contains the solvent vfp.\n",
" \n",
" In the case where solvent_slab is one of the slab materials\n",
" (e.g. fronting or backing) then\n",
" `vfp.shape == (len(structure.slabs()), len(z))`, with\n",
" `vfp[solvent_slab]` containing the vfp for the solvent.\n",
" \"\"\"\n",
" _slabs = structure.slabs()\n",
"\n",
" vf = 1 - _slabs[:, 4]\n",
" \n",
" if solvent_slab is None:\n",
" nvfp = len(_slabs) + 1\n",
" else:\n",
" nvfp = len(_slabs)\n",
" \n",
" z, sldp = sld_profile(_slabs) \n",
" vfp = np.zeros((nvfp, len(z)), float)\n",
" \n",
" for i in range(len(_slabs)):\n",
" _slabs[:, 1:3] = 0\n",
" _slabs[i, 1] = vf[i]\n",
" _vfp = sld_profile(_slabs, z=z)[1]\n",
" vfp[i] = _vfp\n",
" \n",
" # fix up the solvent vfp\n",
" _slabs[:, 1] = 1 - vf\n",
"\n",
" if solvent_slab is None:\n",
" _vfp = sld_profile(_slabs, z=z)[1]\n",
" vfp[-1] = _vfp\n",
" else:\n",
" _slabs[solvent_slab, 1] = 1\n",
" _vfp = sld_profile(_slabs, z=z)[1]\n",
" vfp[solvent_slab] = _vfp\n",
"\n",
" return z, vfp"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "d4236c8a",
"metadata": {},
"outputs": [],
"source": [
"z, vfp = create_vfp(s, solvent_slab=-1)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "e2092a75",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for i in range(len(vfp)):\n",
" plt.plot(z, vfp[i])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "291db8c0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(4, 500)"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vfp.shape"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
@andyfaff
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@igresh @haydenrob @llimeht this might come in useful at some point. (don't use for brushy type components)

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