periodic-boundary-exercise.ipynb

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   "source": [
    "# Task \n",
    "Your task is to calculate the distance of two carbon atoms in an iron matrix, considering periodic boundaries. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Code"
   ]
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  {
   "cell_type": "markdown",
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   "source": [
    "Import required packages "
   ]
  },
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   "source": [
    "from ase.build import bulk\n",
    "import nglview\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Function to display atoms"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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    "ExecuteTime": {
     "end_time": "2018-10-15T13:11:35.812039Z",
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   "source": [
    "def display_atoms(atoms):\n",
    "    view = nglview.show_ase(atoms)\n",
    "    view.add_unitcell()\n",
    "    view.add_spacefill()\n",
    "    view.remove_ball_and_stick()\n",
    "    return view"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create iron bluk matrix (without periodic boundaries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T13:11:35.851979Z",
     "start_time": "2018-10-15T13:11:35.813910Z"
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   "outputs": [],
   "source": [
    "basis = bulk(name='Fe', cubic=True)\n",
    "basis_repeated = basis.repeat([5,5,5])\n",
    "display_atoms(basis_repeated)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Place carbon substitutionals in iron matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
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   },
   "outputs": [],
   "source": [
    "element_lst = basis_repeated.get_chemical_symbols()\n",
    "element_lst[0] = 'C'\n",
    "element_lst[-1] = 'C'\n",
    "basis_repeated.set_chemical_symbols(element_lst)\n",
    "display_atoms(basis_repeated)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Helpful properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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     "end_time": "2018-10-15T13:11:35.946702Z",
     "start_time": "2018-10-15T13:11:35.922524Z"
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   },
   "outputs": [],
   "source": [
    "basis_repeated.positions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "ExecuteTime": {
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     "start_time": "2018-10-15T13:11:35.948609Z"
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   "outputs": [],
   "source": [
    "basis_repeated.cell"
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     "start_time": "2018-10-15T13:11:35.961340Z"
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   },
   "outputs": [],
   "source": [
    "basis_repeated.get_chemical_symbols()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T13:11:35.982864Z",
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   "outputs": [],
   "source": [
    "elements_array = np.array(basis_repeated.get_chemical_symbols())"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T13:11:35.992908Z",
     "start_time": "2018-10-15T13:11:35.984732Z"
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   },
   "outputs": [],
   "source": [
    "selection_index = elements_array=='C'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-10-15T13:11:36.090524Z",
     "start_time": "2018-10-15T13:11:35.994789Z"
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   },
   "outputs": [],
   "source": [
    "basis_repeated.positions[selection_index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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