notebooks/2013-01-01-Calculating XRD patterns.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction\n",
    "\n",
    "This notebook shows how to plot an XRD plot for the two polymorphs of CsCl ($Pm\\overline{3}m$ and $Fm\\overline{3}m$). You can also use matgenie.py's diffraction command to plot an XRD pattern from a structure file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Uncomment the subsequent lines in this cell to install dependencies for Google Colab.\n",
    "# !pip install pymatgen==2022.2.27"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up some imports that we will need\n",
    "from __future__ import annotations\n",
    "\n",
    "from IPython.display import Image, display\n",
    "from pymatgen.analysis.diffraction.xrd import XRDCalculator\n",
    "from pymatgen.core import Lattice, Structure\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# $\\alpha$-CsCl ($Pm\\overline{3}m$)\n",
    "\n",
    "Let's start with the typical $\\alpha$ form of CsCl."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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WLHBgpq6pZ8+ehoeHhzFjxgyr20yfPt0wmUxGz5497ZgZAFgWEBBgPPXUU2bx9u3bGx4eHln+HGjUqJHx6KOP2js9p7LlvVm7r9hITk5W1apVzZb3GYahRx55REuWLFHDhg0tts3Oio3//Oc/evfdd5WSkmLW9oknntDatWtz6TtzH+fOnVPZsmVzpa9mzZpp69atmWIeHh66cOGC2Z1kWXn88ce1f//+TLHg4GDt3r1bnp6eVvWRkpKievXq6cCBA2Z9792716o+LGHFxp+4CxCuiLkK5C27d+/WRx99pBUrVujmzZsWrylcuLCefvppvfvuu1lujYncU6hQId29e1cjR46Ul5f1R/HNmDFD58+fZ8WGnfDzD8j7nnjiCW3ZskXbtm2z+uddVFSUQkND1bx5c61bt87OGbq2qKgoNW3aVKmpqWrbtm3GatAKFSpkrAhNSkrSmTNnMlaDrl27Vp6envr999/5HQOAwxUoUEB/+ctfNHfu3EzxF198UXPnztWdO3csvkfas2dPLV++XLdu3XJUqg5ny3uzdj08XJIKFiyoiRMn6i9/+UvGAeImk0kmk0kXL15Us2bNNGDAAI0ZM0alS5fO9jgbN27U2LFjtX79+owx7uXt7a2JEyfm8LtxT7lV1JCkt99+W927d88US0tL06pVq/TCCy88tP2WLVvMihqSNHr0aKuLGpLk5eWl0aNHm525kb733MO2OQMAAM5Vr149/fjjj7p7967++OMPnTx5UtevX5ckFSlSRJUqVVLNmjU5GM+BgoODFR0drWeffVbBwcFWt/v55591/vx5O2YGAHnbnj179OSTT9r0Bnv9+vUVFhZm8/ZLeVH9+vU1b948vfTSS1q9erXWrFnzwOsNw1DhwoUVGRlJUQOAUxQrVixja8F7eXj8eRx2Vu+RFihQgL+P7mH3wob0ZzWpb9++mjNnjllxIyUlRVOnTtWMGTPUpk0bdevWTXXr1tVjjz1msa+7d+/q8uXLio+P19GjR7Vx40atXbs24+Do+4sa6V+PHTvWpj/QYFnbtm0z/h/e6/Tp01a1/+6778xigYGBZsUSa/To0UPFixc3+4dg3rx5FDYAAHAT3t7eql27tmrXru3sVPK9Bg0aKDo6WlFRUfzeDAAOdOfOnYyzNGzh6+urO3fu2CEj99OzZ081b95cEyZM0OLFi3Xs2DGL11WrVk3dunXTG2+8oTJlyjg4SwD4U5kyZRQTE2MW7927t+rVq5dlu7Nnz7Jq9x4OKWxI0tSpU3XixAlt3rzZrLhhGIZSUlL0yy+/6JdffsnU7t430A3DUP369c36vvea+1dqmEwm/fWvf9Xbb7+dy99R/uTn52exqmjtYVsrV640i3Xu3Dlb1UZvb2917txZkZGRDx0DAAAAD9agQQNNnz5dUVFR6tu3r9Xt7LyzLQDkedWqVdO6deuUkJCQcYjsw8THx2vdunWqWrWqnbNzH2XKlFFERIQiIiJ048YNnTp1KtNq0IoVK6pIkSJOzhIApLp16+rbb7/V1atXVbRo0Yx427Zt1bZtW4ttkpOTFR0drVatWjkoS9fn4aiBChYsqJUrV6pVq1ZmqyruLXDc+2HJ/dekX3dvH/de27VrV82ZM8e+31w+Y6kIkb5U6kFiYmJ0/Phxs3hYWFi2c7HU9tixYxarngAAwHXMnTtX7dq1U1BQkJ588klNnjxZKSkpWV7/9ttv8+aNnXXs2FETJkzQk08+aVO7xYsX68SJE3bKCgDyvueee04JCQl68sknrdpaauvWrQoLC9PVq1fVp08fB2Tofvz8/BQcHKzQ0FCFhoYqODiYogYAl9G+fXuFhobq6NGjVrdZsGCBkpKS1LJlSztm5l4ctmJD+nOZ5Nq1a/X6669rypQpFldX3MtSceP+a+699v7ixrBhwzR+/Hir3nSHdZKSkhQbG2sWt2YJ544dOyzGmzRpku18GjdubDG+a9culS9fPtv9AgAA+xk8eLCmTZuW8TvbkSNHtHHjRk2fPl3z58+3WMC4cuWKTp065eBM85dy5cpp2LBhNrd75JFH7JANAOQfw4cP15IlS7R161Y1b95cFSpUeODh12fOnJFhGGrWrJmGDx/u5OwBALbq3bu3evfubVObkJAQrV+/ni187+HQwob056HPkydPVqdOnfTaa6/p5MmTFosVD1qxca/0tun/NQxD5cqV03//+189/fTTuZw9Nm7cqLS0NLN4tWrVHtp27969ZjEfH58c3X1ZvXp1FSpUSLdv384U37Nnj7p27ZrtfgEAgH2sWLFCU6dOlaenp1566SWFhITo6NGjioyM1J49e9SsWTOtWbNGderUcXaqAAA4hLe3t9auXasRI0ZoypQpOn36tE6fPp3lzZ8FChTQ4MGD9dFHH8nLy+Fv6+QZu3fv1rVr19jWBYBbCAoKUlBQkLPTcClO+wkYHh6uw4cPa+bMmfr88891+PDhjMfSV15YK/2He9myZTV06FC9/vrrKlSoUK7nDGn27NlmMW9vb7Vr1+6hbS1tQ1WlShWb/l/fz2QyqUqVKjp48GCmONshAADgmqZOnSqTyaR58+apV69eGfF3331Xffr00bp16xQWFqbVq1crJCTEiZkCAOA4Pj4+mjhxov75z39qxYoVio6O1smTJzOdEVGpUiXVr19fHTt2zLQnO7Jn8ODB2rFjxwO3wgQAuC6nlva9vb01aNAgDRo0SNu2bdNPP/2k1atXa//+/bp7965VfVSsWFFhYWHq1q2bOnToIE9PTztnnX/t2bNHCxcuNIs/8cQTCggIeGh7S9tHlC1bNsd5lS1b1qywwVYVAAC4pu3btys4ODhTUUOSSpcurVWrVunVV1/VrFmz1LZtW61evVr169d3Uqb519y5czVnzhzFxMSoTJky6tmzpwYOHJjlXcFvv/22Fi5caPEmFgCAbYoWLZqtLUqQPVntFgIAcH0us2axadOmatq0qT7++GPduXNHhw8f1unTp3X+/Hldv35dycnJ8vDwUOHChRUYGKgKFSooKChIJUuWdHbq+UJqaqoGDRpkcRuqt99+26o+LJ3NUbp06RznZmlfZ0tjAQAA54uLi1ObNm0sPubp6akZM2bI19dXX3zxhdq2bas1a9ZQ3HAgzj8BAAAA4A5cprBxrwIFCqhOnTrsrexC/vWvf2nbtm1m8aefflpPPfWUVX3Ex8ebxaxZ6fEw/v7+ZrG4uDir2iYnJys5OTnj62vXruU4HwAAkDVfX18lJSU98JpJkybJy8tLEyZMyFi5Afvj/BMAcB23bt3SqVOnMv5G9ff3V8WKFVW4cGEnZ+Z6Bg4cmK12bGENAO7NJQsbcC2rVq3SBx98YBYPCAjQ5MmTre7nxo0bZjE/P78c5Sb9+QbJ/R72hkm6jz/+2OL3BgAA7KN69eratWvXQ68bP368PD099dlnn6ldu3aqVq2aA7LL3zj/BACc6/Lly5o0aZIWLlyoo0ePmm2TZDKZVL16dfXo0UOvv/66SpUq5aRMXcuMGTNkMpmyta1UTs78BAA4F4UNPNDBgwf17LPPWtyCasqUKapQoYLVfVk6NyWrvZpt4e3tbRa7c+eOVW1HjBih4cOHZ3x97do1lS9fPsc5AQAAy1q3bq3//Oc/2rJli5o1a/bAayMiIuTh4aGIiAjt3LnTQRnmX5x/AgDO89NPP6lv3766ceNGlm/QG4ahI0eO6OOPP9aXX36pOXPmqHPnzg7O1PUUKFBAd+/e1ahRo2x6j2HGjBk6f/68HTMDANgThQ1k6dy5c+rYsaMSExPNHhs6dKj++te/2tRfamqqWSw3Dnu31EdKSopVbQsWLKiCBQvmOAcAAGCd8PBwjR8/XhMnTnxoYUOSPvnkE3l5eemjjz7irko74/wTAHCO6Oho9erVSykpKQoLC1Pv3r3VsGFDlS9fPmOXgxs3bigmJkY7d+7Ut99+q3Xr1qlXr176/fffVa9ePed+A04WHBys6OhoPfvsswoODra63c8//0xhAwDcmF0LGzdv3rR4d12rVq3sOazLjO/OYmNj1a5dO50+fdrssS5dumjChAk29+nl5WW2asPaAsSDWOrD0ioOAADgfK1atdKaNWvk4eFhdZtx48apSZMmFs/rQu7h/BMAcI6PP/5YKSkpmjZtmgYMGGDxmqJFi6po0aJ6/PHH1a9fP02bNk2DBg3SRx99pB9//NHBGbuWBg0aKDo6WlFRUTYVNgAA7s2uhY2TJ0+qTZs2me6uM5lMufJmtjuM764SEhLUrl07HTx40Oyxdu3a6YcffsjWSouCBQuaFTas3TLqQSz1wSoMAABck5eXl8LCwmxu16lTJztkg3tx/gkAOMemTZvUuHHjLIsalgwcOFCzZs3Spk2b7JiZe2jQoIGmT5+uqKgo9e3b1+p22TmTAwDsKS0tTXFxcZligYGBNt0Ulp845FkxDCPTh6M5e3x3cu3aNbVv3167d+82e6x169ZavHhxtosGRYoUMYtdv349W309rA9/f/8c9wsAAJCftG7dWhcvXtSWLVseem1ERITeeecdJSQkcP4JAOTQ1atXVblyZZvbVa5c2eLW0flNx44dNWHCBD355JM2tVu8eLFOnDhhp6wAwHZxcXEqVapUpo/7Cx34Pw4pbJhMJqfuiezs8d3FjRs3FB4erh07dpg91qxZMy1btkw+Pj7Z7j8wMNAsdvXq1Wz396A+LI0FAACArIWHh8swDE2cONGq6z/55BONHDmSG4cAIIceffRR7dy506Z/T9PS0rRjxw6VKVPGjpm5h3LlymnYsGE2H6T+yCOPqGLFinbKCgBgb6xjgSQpKSlJHTt2tHiHXuPGjbVy5cqMQ8uy65FHHjGLXbx4MUd9ZtWHpbEAAACQtfTzTwYPHmx1m3Hjxumnn37SrFmz7JgZAORtHTt21IkTJ/Tyyy/r5s2bD73+1q1b6t+/v06ePKlnnnnGARkCAOB67HrGBtzDzZs39cwzz+jXX381e6x+/fpatWpVrmztZGlp7ZkzZ3Lcr6U+srOMFwAAID/j/BMAcI73339f//vf/zRnzhwtWbJEnTt3VsOGDVWhQgX5+vpK+vNmxDNnzmjnzp1asmSJrl69qpIlS2r06NFOzt49JCcna+fOnbp8+bJq1Kih2rVrOzslAEAOUdjI527duqXOnTtrw4YNZo/VqVNHa9asUdGiRXNlrOrVq5vFTp8+rTt37qhAgQLZ6jM5OdliYcPSWAAAAAAAuJpSpUrp119/1V//+lft3r1bX3/9tebMmWPx2vTtqkJCQvTdd9+pVKlSjkzVZV28eFFvvfWWVq9erYIFC6pLly765JNPVKRIEW3evFnPP/+8YmJiMq4PDQ3V999/r3LlyjkxawBATuTpwsadO3fMYpwi/39u376tLl266JdffjF7LDg4WL/88ouKFy+ea+OFhISYxVJTU7V//37Vr18/W33u27dPqampZvF69eplqz8AQN6zcuVKxcbGqm/fvs5OBQAAwKIaNWooKipKK1eu1KJFixQdHa2TJ0/q+vXrkqQiRYqoUqVKql+/vrp166bw8HAnZ+w6kpKS1KpVKx0/fjyj8DNlyhSdPn1as2fPVteuXZWQkKBatWrJ19dXe/bs0ZYtWxQeHq6oqCh5e3s7+TsAAGRHni5sXLt2zSxWqFAhJ2TiepKTk9W9e3etWbPG7LGgoCD98ssvKlGiRK6O2bBhQ3l4eCgtLS1TfMuWLdkubGzdutUs5unpqQYNGmSrPwBA3vPhhx9q+/btFDYAAIDLCw8Pp2hhoy+++ELHjh1TixYt9NFHH8nLy0tjxozRypUrNXz4cBmGoa1bt6px48aSpCtXrqhXr17atGmTIiMj9corrzj5OwAAZEeeXr5w9OhRs1ixYsWckIlruXPnjnr27KmVK1eaPVazZk2tW7fOLstZixYtqoYNG5rFV61ale0+LbVt2LBhrm2fBQAAAAAAXNeiRYtUuHBh/fTTT2rRooWaNm2qBQsWyM/PT/PmzdN7772XUdSQpBIlSmjq1KkymUxasGCBEzMHAOREni5srFu3LuNzwzBkMpny/f6JKSkpevbZZ7Vs2TKzx2rUqKH169frkUcesdv4lg6XXL16tRISEmzuKz4+3uKKk86dO2crNwAA4DxpaWmKjY3N9HH/Kk8AAID7HTlyRKGhoZluZPXz81NoaKgkqUuXLmZtatSoofr162vfvn0OyxMAkLvy7FZU+/bt06JFi2QymTLFH3vsMSdl5Hypqal67rnntHjxYrPHqlWrpnXr1qlMmTJ2zaFPnz56//33M/a9lP5cQTJ16lS9++67NvU1bdo0s3NUTCaTevfunSu5AgBcS7t27bLV7tChQ7mcCewhLi7ObMXo5cuXVbJkSSdlBACwxZo1a7Rw4cKMsyHSt4b29/fPOBuie/fuatu2rZMzdV2JiYnavHmzChYsqKZNm8rPzy/jsRUrVmjRokW6fPmyatSooX79+qlWrVpOzNZ13Lx5U6VLlzaLp8cqVKhgsV2FChUobACAG8tThY3bt2/r0KFDWrp0qSZMmKDk5GSzwkaTJk2clJ1zpaWlqW/fvpo/f77ZY1WqVNH69etVtmxZu+dRuXJldezYUcuXL88U//e//61XXnlFgYGBVvVz5coVRUREmMWfeeYZVapUKTdSBQC4mLVr18pkMmUqjlvr/t8HAABA7jhx4oR69+6tHTt2SJLZz+n0VXg7duzQtGnT1LhxY82bN0+VK1d2Rrou64cfftCAAQN08+ZNSX++KT9//nw1a9ZM77zzjsaPH5/puf388881e/ZsbuzTn1uOx8fHm8U9PP7cpMTT09NiuwIFCnBwOAC4sWwVNiZNmqRJkyY99Lq7d+9ajFepUiU7w2bpzp07unXrlq5evZoRS996Kv2/6Tp27JirY7sDwzDUv39/zZs3z+yxypUra/369Q7domv06NFmhY34+Hj169dPixcvzvjlIyupqanq16+f2fZVJpNJo0aNyvV8AQCuwcfHR7dv39aUKVNUsGBBq9uNHTtWJ0+etGNmAADkT7GxsWrevLkuXbqkgIAAde7cWQ0bNlT58uUzVhvcuHFDMTEx2rlzp5YuXarff/9dLVq00O7du1mV9//t379fL7zwglJSUlSlShV5eXnpjz/+UK9evfTdd9/ps88+U7169dSnTx/5+vpq7dq1WrhwoQYMGKBmzZrl+5v7ypQpo5iYGLN47969Va9evSzbnT17ljkIAG4sW4WNq1ev6tSpU1Zff+9dBYZh2NQ2u9KLGfcWN9q3b6/y5cvbfWxXM3ToUEVGRprFCxcurI8//ljnz5/X+fPnczRGwYIFFRISYtW1TZs2Vd++fTVnzpxM8aVLl6pPnz6aOXOmChcubLFtUlKSXn75ZYtnhPTt2zffrsgBgPygXr162rZtmxo2bKj69etb3W7KlCkUNoAcSktLU1xcXKZYYGDgQ29IAZC3jR07VpcuXdILL7ygyZMny9fX94HXJyUlafDgwZo7d67GjRtn1Q2T+cHEiROVkpKizz77TMOHD5f059bLgwYNUv/+/dW0aVNt2rRJXl5/voUzaNAgjRs3Tu+//76mTJmiTz75xJnpO13dunX17bff6urVqypatGhGvG3btllufZacnKzo6Gi1atXKQVkCAHJbjraismZbB0vbRThjOwhvb+98+8PeUhFA+nMfyr/+9a+5MkbFihVtKlhNmjRJmzZtMmvz/fffa8uWLXrzzTcVHh6ecefJiRMn9PPPP+s///mPzp49a9Zf5cqVNXHixOx/AwAAl9egQQNt27ZNUVFRNhU2AOQcZ6AAsGTZsmWqWrWqIiMjrfo739fXV5GRkdqyZYuWLl1KYeP/27hxoypVqpRR1JCkgQMH6rPPPtPx48f15ZdfZhQ10r311luaMGGC1q5d6+h0XU779u114sQJHT16VI0aNbKqzYIFC5SUlKSWLVvaOTsAgL3k+VusDMOQp6enpk+frjp16jg7Hfx/RYsW1ZIlS1S8eHGzx86cOaM333xTjz32mAoVKqRChQqpVq1aGj58uMWiRmBgoJYsWZLpzgwAQN7ToEEDGYahqKgom9oZhpGtczkAAMCDXbhwQQ0bNrTp5kUPDw81atRIFy5csGNm7uXcuXN6/PHHzeLBwcGSZPGGDh8fH9WtW1fHjx+3e36urnfv3vr111+tLmpIUkhIiNavX68BAwbYMTMAgD3lycJG+hsYhmGoYcOG2rRpk1544QVnp4X7PP7449qwYUOODo2rUqWKNmzYkPELHwAg7+rUqZMWLVqkvn372tRu27ZtSktLs1NWAADkXwEBAdna7vHUqVMKCAiwQ0buyWQyWdyOOf05ymp1XJkyZZSUlGTX3PKqoKAgtW7dWiVKlHB2KgCAbMpRYePeAkJWH9ltl50PSSpdurSeeOIJjRo1Sr///ru2b9+u0NDQnHybsKPHH39cu3bt0qBBg+Tp6Wl1O09PTw0ePFi7du2iqAEA+UTx4sXVpUsXNW3a1NmpAAAASS1bttSOHTs0c+ZMq9vMmDFDv//+O1sA3aNEiRK6ePGiWfxhq05v377NzgUAgHzLZGRjb4bExERdvXr1odcdOXJEHTp0yFiWmn6I94kTJ2xO9EE8PT1VqFAhFStWzKY3x+Fazpw5o5kzZ2r58uXas2ePUlJSMj3u5eWlunXr6umnn1b//v1VoUKFXM/h2rVrCggIUGJiovz9/XO9f1cUGxvLntlwC8xVIG/jNe7a+P/jPDz3cGVRUVFq2rSpUlNT1bZtWz333HNq2LChKlSokHGQeFJSks6cOaOdO3dq3rx5Wrt2rTw9PfX7778rJCTEyd+Ba2jdurWOHj2q8+fPZ4rfunVLd+7cyXJ1S3BwsDw8PLR3715HpAkAsDN+77PtvdlsHR4eEBBg1bLRGzduWIxXrFgxO8Mij6tQoYI++OADffDBB7p7967OnDmjxMRESX/OuQoVKsjb29vJWQIAAAAApD/Pfpg3b55eeuklrV69WmvWrHng9YZhqHDhwoqMjKSocY+QkBBt3rxZf/zxh2rUqJER9/HxkY+Pj8U2Z8+e1aFDh/Tiiy86Kk0AAFxKtgobgL15e3uratWqzk4DAJAH7N69W9euXVOrVq2cnQoAAHlOz5491bx5c02YMEGLFy/WsWPHLF5XrVo1devWTW+88YbKlCnj4Cxd26uvvqrHH39chQoVsrrNggULVKFCBbVr186OmQEA4LocUtjIxm5XAAAAuWLw4MHasWOH2RaHAAAgd5QpU0YRERGKiIjQjRs3dOrUKV2/fl2SVKRIEVWsWFFFihRxcpauKygoSEFBQTa1GTZsmIYNG2anjAAAcH12LWyUKlVKY8aMsecQAAAAD8VNFgAAOIafn5+Cg4OdnQYAAMjj7FrYKFmyJIUNAAAAAAAAAACQazhjAwAAuIWBAwdmq92JEydyORMAAADn2rRpk7y9vdW0aVOZTCZnp+OS0tLSFBcXlykWGBgoDw8PJ2UEAMhNFDYAAIBbmDFjhkwmU7a2leIPfgAA7CMlJUWffPKJ5syZo5iYGJUpU0Y9e/bUiBEjVKxYMYtt+vXrp2+++Ybzr3KgTZs2MplMCg4O1kcffaSnn37a2Sm5nLi4OJUqVSpT7PLlyypZsqSTMgIA5CYKGwAAwC0UKFBAd+/e1ahRo+TlZf2vMDNmzND58+ftmBkAAPlX9+7dtXz58owbD06dOqXx48fr+++/148//qimTZtabMf5VzlnGIb27dunzp07q0WLFtq4caOzUwIAwGEobAAAALcQHBys6OhoPfvsszYdSvrzzz9T2AAAwA7mzZunZcuWydfXV++++65CQkJ09OhRff755zp58qTCwsK0ePFitW3b1tmp5jlpaWkyDEO7du3SqlWrtGbNGmenBACAQ7GxIAAAcAsNGjSQJEVFRTk5EwAAIEmRkZEymUxasWKFRo0apY4dO2rYsGHav3+/+vbtq1u3bql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      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create CsCl structure\n",
    "a = 4.209  # Angstrom\n",
    "latt = Lattice.cubic(a)\n",
    "structure = Structure(latt, [\"Cs\", \"Cl\"], [[0, 0, 0], [0.5, 0.5, 0.5]])\n",
    "\n",
    "c = XRDCalculator()\n",
    "ax = c.get_plot(structure)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare it with the experimental XRD pattern below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(Image(filename=(\"./PDF - alpha CsCl.png\")))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# $\\beta$-CsCl ($Fm\\overline{3}m$)\n",
    "\n",
    "Let's now look at the $\\beta$ (high-temperature) form of CsCl."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create CsCl structure\n",
    "a = 6.923  # Angstrom\n",
    "latt = Lattice.cubic(a)\n",
    "structure = Structure(\n",
    "    latt,\n",
    "    [\"Cs\", \"Cs\", \"Cs\", \"Cs\", \"Cl\", \"Cl\", \"Cl\", \"Cl\"],\n",
    "    [\n",
    "        [0, 0, 0],\n",
    "        [0.5, 0.5, 0],\n",
    "        [0, 0.5, 0.5],\n",
    "        [0.5, 0, 0.5],\n",
    "        [0.5, 0.5, 0.5],\n",
    "        [0, 0, 0.5],\n",
    "        [0, 0.5, 0],\n",
    "        [0.5, 0, 0],\n",
    "    ],\n",
    ")\n",
    "\n",
    "ax = c.get_plot(structure)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare it with the experimental XRD pattern below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(Image(filename=(\"./PDF - beta CsCl.png\")))"
   ]
  }
 ],
 "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}