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   "source": [
    "### Solcore - Schrodinger_QW_absorption\n",
    "\n",
    "***\n",
    "\n",
    "Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from solcore import si, material\n",
    "from solcore.structure import Layer, Structure\n",
    "import solcore.quantum_mechanics as QM\n",
    "from solcore.constants import vacuum_permittivity, q"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we create the materials we need"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bulk = material(\"GaAs\")(T=293, strained=False)\n",
    "barrier = material(\"GaAsP\")(T=293, P=0.1, strained=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As well as some of the layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_layer = Layer(width=si(\"30nm\"), material=bulk)\n",
    "inter = Layer(width=si(\"3nm\"), material=bulk)\n",
    "barrier_layer = Layer(width=si(\"15nm\"), material=barrier)\n",
    "bottom_layer = top_layer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are going to calculate the absorption coefficient of InGaAs QWs of fixed thickness but different compositions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_comp = 5\n",
    "comp = np.linspace(0.05, 0.25, num_comp)\n",
    "colors = plt.cm.jet(np.linspace(0, 1, num_comp))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The absorption coefficients will be calculated at these energies and stored in alfas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_energy = 300\n",
    "E = np.linspace(1.15, 1.5, num_energy) * q"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We define some parameters need to calculate the shape of the excitonic absorption"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha_params = {\n",
    "    \"well_width\": si(\"7.2nm\"),\n",
    "    \"theta\": 0,\n",
    "    \"eps\": 12.9 * vacuum_permittivity,\n",
    "    \"espace\": E,\n",
    "    \"hwhm\": si(\"6meV\"),\n",
    "    \"dimensionality\": 0.16,\n",
    "    \"line_shape\": \"Gauss\"\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "# plt.figure(figsize=(4, 4.5))\n",
    "for j, i in enumerate(comp):\n",
    "    # We create the QW material at the given composition\n",
    "    QW = material(\"InGaAs\")(T=293, In=i, strained=True)\n",
    "\n",
    "    # And the layer\n",
    "    well_layer = Layer(width=si(\"7.2nm\"), material=QW)\n",
    "\n",
    "    # The following lines create the QW structure, with different number of QWs and interlayers\n",
    "    test_structure = Structure([barrier_layer, inter, well_layer, inter, barrier_layer], substrate=bulk)\n",
    "\n",
    "    # Finally, the quantum properties are claculated here\n",
    "    output = QM.schrodinger(test_structure, quasiconfined=0, num_eigenvalues=20, alpha_params=alpha_params,\n",
    "                            calculate_absorption=True)\n",
    "\n",
    "    alfa = output[0]['alphaE'](E)\n",
    "    plt.plot(1240 / (E / q), alfa / 100, label='{}%'.format(int(i * 100)))\n",
    "\n",
    "plt.xlim(826, 1100)\n",
    "plt.ylim(0, 23000)\n",
    "plt.xlabel('Wavelength (nm)')\n",
    "plt.ylabel('$\\\\alpha$ cm$^{-1}$')\n",
    "plt.legend(loc='upper right', frameon=False)\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  }
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