notebooks/5 pH.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import overreact as rx"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "model = rx.parse_model(\"../../overreact/data/acetate/model.k\")\n",
    "k = rx.get_k(model.scheme, model.compounds)\n",
    "model.scheme.compounds"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "WARNING:overreact.thermo._gas:assuming zero rotational energy for atomic system\n",
      "WARNING:overreact.thermo._gas:assuming zero vibrational energy for atomic system\n",
      "WARNING:overreact.thermo._gas:assuming zero rotational entropy for atomic system\n",
      "WARNING:overreact.thermo._gas:assuming zero vibrational entropy for atomic system\n",
      "WARNING:overreact.thermo._gas:assuming ground state as electronic energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming zero point as vibrational energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming ground state as electronic energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming zero point as vibrational energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming ground state as electronic energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming zero vibrational energy for atomic system\n",
      "WARNING:overreact.thermo._gas:assuming ground state as electronic energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming zero point as vibrational energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming ground state as electronic energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming zero point as vibrational energy at zero temperature\n",
      "WARNING:overreact.thermo._gas:assuming rotational energy zero at zero temperature\n"
     ]
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "('AcOH(aq)', 'AcO-(aq)', 'H+(aq)', 'AcOH(g)', 'AcO-(g)')"
      ]
     },
     "metadata": {},
     "execution_count": 11
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "source": [
    "Y = []\n",
    "pHs = np.linspace(0, 14)\n",
    "for pH in pHs:\n",
    "    scheme, kobs = rx.get_fixed_scheme(model.scheme, k, {\"H+(aq)\": 10**-pH})\n",
    "    dydt = rx.get_dydt(scheme, kobs)\n",
    "    y, _ = rx.get_y(dydt, [0.5, 0.0, 0.0, 0.0])\n",
    "    Y.append(y(y.t_max))\n",
    "Y = np.asarray(Y)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "for i, compound in enumerate(scheme.compounds):\n",
    "    if \"(aq)\" in compound:\n",
    "        plt.plot(pHs, Y[:, i], label=compound)\n",
    "\n",
    "plt.vlines(4.756, 0.0, 0.5, label=r\"exp. $pK_a$\", color=\"k\")\n",
    "plt.xlabel(\"pH\")\n",
    "plt.ylabel(\"Concentration (mol/L)\")\n",
    "plt.legend()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1509e4156c70>"
      ]
     },
     "metadata": {},
     "execution_count": 9
    },
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"
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     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  }
 ]
}