{ "cells": [ { "cell_type": "markdown", "id": "c91c0b81-e809-40ab-abfe-a27d614e5793", "metadata": {}, "source": [ "## Initial imports" ] }, { "cell_type": "code", "execution_count": 1, "id": "f8ac58ba-d867-4345-96a4-41c07815c7d5", "metadata": {}, "outputs": [], "source": [ "from scm.plams import *\n", "\n", "try:\n", " from ase import Atoms\n", " from pymatgen.core.structure import Structure\n", " from pymatgen.analysis.diffraction.xrd import XRDCalculator\n", "except ImportError as e:\n", " print(\n", " \"You need ASE and pymatgen installed in the AMS python environment to run this example. Install the package for m3gnet to do this.\"\n", " )\n", " print(e)\n", " exit(1)" ] }, { "cell_type": "markdown", "id": "552d14e3-6331-49b6-98b0-8c826923b62d", "metadata": {}, "source": [ "## Create ASE atoms object for BaTiO3" ] }, { "cell_type": "code", "execution_count": 2, "id": "efbc31f3-35c6-457d-9cab-fc2b6c0b30aa", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "at = Atoms(\n", " symbols=[\n", " \"Ba\",\n", " \"Ti\",\n", " \"O\",\n", " \"O\",\n", " \"O\",\n", " ],\n", " scaled_positions=[\n", " [\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " ],\n", " [0.5, 0.5, 0.5],\n", " [0.0, 0.0, 0.5],\n", " [0.0, 0.5, 0.0],\n", " [0.5, 0.0, 0.0],\n", " ],\n", " cell=[4.01, 4.01, 4.01],\n", " pbc=(True, True, True),\n", ")\n", "plot_molecule(at, rotation=\"-5x,5y,0z\"); # show in Jupyter notebook" ] }, { "cell_type": "markdown", "id": "5164dc41-6270-47fc-95ac-cf6e54b88e3e", "metadata": {}, "source": [ "## Save ASE Atoms to .cif format" ] }, { "cell_type": "code", "execution_count": 3, "id": "ab089b83-57ef-45f6-8e0a-585bf4bb942f", "metadata": {}, "outputs": [], "source": [ "fname = \"batio3.cif\"\n", "at.write(fname)" ] }, { "cell_type": "markdown", "id": "d85f4212-0a51-4636-ac11-0e3d6a7a3027", "metadata": {}, "source": [ "## Load .cif in pymatgen and calculate XRD" ] }, { "cell_type": "markdown", "id": "e2718a7f-24ee-4546-9296-56b470bfbb2e", "metadata": {}, "source": [ "Available radiation sources:" ] }, { "cell_type": "code", "execution_count": 4, "id": "5abf4fc1-e438-4f8f-9ad7-bcb808345144", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Available radiation sources: ('CuKa', 'CuKa2', 'CuKa1', 'CuKb1', 'MoKa', 'MoKa2', 'MoKa1', 'MoKb1', 'CrKa', 'CrKa2', 'CrKa1', 'CrKb1', 'FeKa', 'FeKa2', 'FeKa1', 'FeKb1', 'CoKa', 'CoKa2', 'CoKa1', 'CoKb1', 'AgKa', 'AgKa2', 'AgKa1', 'AgKb1')\n" ] } ], "source": [ "print(f\"Available radiation sources: {XRDCalculator.AVAILABLE_RADIATION}\")" ] }, { "cell_type": "markdown", "id": "3a114c7e-d9c1-469a-9638-0eac74bb77d6", "metadata": {}, "source": [ "Let's choose Cu K-alpha (default):" ] }, { "cell_type": "code", "execution_count": 5, "id": "08648011-008b-400c-958f-43321e37c62d", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "structure = Structure.from_file(fname)\n", "xrd_calc = XRDCalculator(wavelength=\"CuKa\")\n", "xrd_calc.show_plot(structure)" ] }, { "cell_type": "code", "execution_count": 6, "id": "d0d901cf-546a-4148-af08-95e5aff2b95d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2*Theta Intensity hkl d_hkl(angstrom)\n", "22.17 46.84 (1, 0, 0) 4.010\n", "31.55 100.00 (1, 1, 0) 2.835\n", "38.90 1.83 (1, 1, 1) 2.315\n", "45.23 34.58 (2, 0, 0) 2.005\n", "50.92 19.69 (2, 1, 0) 1.793\n", "56.19 38.27 (2, 1, 1) 1.637\n", "65.88 20.48 (2, 2, 0) 1.418\n", "70.44 9.47 (2, 2, 1) 1.337\n", "70.44 9.47 (3, 0, 0) 1.337\n", "74.88 16.60 (3, 1, 0) 1.268\n", "79.23 1.68 (3, 1, 1) 1.209\n", "83.51 6.82 (2, 2, 2) 1.158\n", "87.76 4.44 (3, 2, 0) 1.112\n" ] } ], "source": [ "pattern = xrd_calc.get_pattern(structure)\n", "print(\"2*Theta Intensity hkl d_hkl(angstrom)\")\n", "for two_theta, intensity, hkls, d_hkl in zip(pattern.x, pattern.y, pattern.hkls, pattern.d_hkls):\n", " hkl_tuples = [hkl[\"hkl\"] for hkl in hkls]\n", " for hkl in hkl_tuples:\n", " label = \", \".join(map(str, hkl))\n", " print(f\"{two_theta:.2f} {intensity:.2f} {hkl} {d_hkl:.3f}\")" ] } ], "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": "3.8.16" } }, "nbformat": 4, "nbformat_minor": 5 }