{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/prehner/.conda/envs/feos/lib/python3.9/site-packages/pymatgen/core/__init__.py:49: UserWarning: Error loading .pmgrc.yaml: [Errno 2] No such file or directory: '/home/prehner/.pmgrc.yaml'. You may need to reconfigure your yaml file.\n", " warnings.warn(f\"Error loading .pmgrc.yaml: {ex}. You may need to reconfigure your yaml file.\")\n" ] } ], "source": [ "from feos.si import *\n", "from feos.dft import Pore3D, Adsorption3D, DFTSolver, FMTVersion, HelmholtzEnergyFunctional\n", "from feos.pcsaft import PcSaftParameters\n", "\n", "import pandas as pd\n", "import numpy as np\n", "\n", "from pymatgen.core import Structure\n", "from pymatgen.analysis import structure_matcher\n", "\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "formula: Zn12 H120 C96 N48\n", "num_sites: 276\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/prehner/.conda/envs/feos/lib/python3.9/site-packages/pymatgen/io/cif.py:669: UserWarning: A 1-line symmetry op P1 CIF is detected!\n", " warnings.warn(msg)\n", "/home/prehner/.conda/envs/feos/lib/python3.9/site-packages/pymatgen/io/cif.py:1160: UserWarning: Issues encountered while parsing CIF: A 1-line symmetry op P1 CIF is detected!\n", " warnings.warn(\"Issues encountered while parsing CIF: %s\" % \"\\n\".join(self.warnings))\n" ] } ], "source": [ "structure = Structure.from_file('structure_parameters/ZIF-8.cif')\n", "print('formula: ', structure.formula)\n", "print('num_sites:', structure.num_sites)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "coordinates = structure.cart_coords.T * ANGSTROM\n", "system_size = [l * ANGSTROM for l in structure.lattice.lengths]" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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typesigmaepsilonmass
0O3.0330048.158115.99900
1C3.4729947.856212.01070
2H2.846007.64891.00784
3N3.2625038.949214.00670
4B3.5810047.805910.81100
5Zn1.33000109.471065.38000
\n", "
" ], "text/plain": [ " type sigma epsilon mass\n", "0 O 3.03300 48.1581 15.99900\n", "1 C 3.47299 47.8562 12.01070\n", "2 H 2.84600 7.6489 1.00784\n", "3 N 3.26250 38.9492 14.00670\n", "4 B 3.58100 47.8059 10.81100\n", "5 Zn 1.33000 109.4710 65.38000" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "forcefield = pd.read_csv('structure_parameters/DREIDING.dat',delim_whitespace=True,names=[\"type\",\"sigma\",\"epsilon\",\"mass\"])\n", "forcefield" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "sigma = np.zeros(structure.num_sites)\n", "epsilon = np.zeros(structure.num_sites)\n", "\n", "mass = 0.0\n", "\n", "for i, site in enumerate(structure):\n", " sigma[i] = forcefield[\"sigma\"][forcefield[\"type\"]==site.species_string]\n", " epsilon[i] = forcefield[\"epsilon\"][forcefield[\"type\"]==site.species_string]\n", " mass = mass + float(forcefield[\"mass\"][forcefield[\"type\"]==site.species_string]) * 1.6605402E-27" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from mpl_toolkits.mplot3d import Axes3D\n", "fig = plt.figure()\n", "ax = fig.add_subplot(111, projection='3d')\n", "ax.scatter(xs=structure.cart_coords[:,0],ys=structure.cart_coords[:,1],zs=structure.cart_coords[:,2],s=20)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "params = PcSaftParameters.from_json(['methane'], '../../parameters/pcsaft/gross2001.json')\n", "func = HelmholtzEnergyFunctional.pcsaft(params, FMTVersion.AntiSymWhiteBear)\n", "\n", "T = 303 * KELVIN" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$2.369\\times10^{-27}\\,\\mathrm{m^{3}}$" ], "text/plain": [ "2.3689628728234253e-27 m³" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pore = Pore3D(system_size, [64, 64, 64], coordinates, sigma, epsilon)\n", "pore.pore_volume" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "|solver|log|max_iter|tol|beta|mmax|max_rel|\n", "|-|:-:|-:|-:|-:|-:|-:|\n", "|Picard Iteration||50|1e-11|0.01||1|\n", "|Picard Iteration||500|1e-5|0.1||1|\n", "|Anderson Mixing||150|1e-8|0.15|10||" ], "text/plain": [ "Picard Iteration (max_rel=1) max_iter: 50, tol: 0.00000000001, beta: 0.01\n", "Picard Iteration (max_rel=1) max_iter: 500, tol: 0.00001, beta: 0.1\n", "Anderson Mixing (mmax=10) max_iter: 150, tol: 0.00000001, beta: 0.15" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "solver = DFTSolver().picard_iteration(damping_coefficient=0.01,max_iter=50).picard_iteration(damping_coefficient=0.1,tol=1.0e-5).anderson_mixing(mmax=10,tol=1.0e-8)\n", "solver" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 17min 11s, sys: 2min 13s, total: 19min 25s\n", "Wall time: 19min 18s\n" ] } ], "source": [ "%%time\n", "pressure = SIArray1.linspace(100*PASCAL, 50*BAR, 20)\n", "isotherm = Adsorption3D.adsorption_isotherm(func, temperature = T, pressure = pressure, pore=pore, solver=solver)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'N')" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(isotherm.pressure/BAR, isotherm.total_adsorption*NAV)\n", "plt.axis([0,50,0,17.5])\n", "plt.xlabel('p / bar')\n", "plt.ylabel('N')" ] } ], "metadata": { "kernelspec": { "display_name": "feos", "language": "python", "name": "feos" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.10" } }, "nbformat": 4, "nbformat_minor": 5 }