{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Langmuir Isotherm\n", "----\n", "\n", "Reproduce the Langmuir isotherm directly from numerical results from MECSim using a mechanism that mimics adsorption by using a pre-existing surface confined species rather than the assumption of free and taken sites on the electrode. In practice these are the same thing, which is why MECSim reproduces the isotherm without in-built assumptions.\n", "\n", "The Langmuir isotherm gives the surface converage of substrate A as:\n", "$$\n", "\\theta_A = \\frac{K_{eq}^A A}{1 + K_{eq}^A A}\n", "$$\n", "where $A$ is the concentration of solution species A (mol/cm$^3$) and $K_{eq}^A = k_f/k_b$ for the reaction\n", "$$\n", "A + B^* = A^*\n", "$$\n", "where $^*$ denotes a surface confined species, $A^*$ is the substrate version of $A$ in solution, and $B^*$ can be thought of as a pre-existing surface species (as MECSim does) or as an empty site (as Langmuir assumed)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# import required python packages\n", "%matplotlib inline\n", "import numpy as np\n", "from matplotlib import cm\n", "import matplotlib.pyplot as plt\n", "from latexify import *" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# results from single parameter sweep over concentration of A\n", "f = open('results_VaryA.txt', 'r')\n", "x = []\n", "y = []\n", "xplotmax = 0.0\n", "yplotmax = 0.0\n", "for line in f:\n", " columns = line.split()\n", " x.append(float(columns[0]))\n", " y.append(float(columns[1]))\n", " xplotmax = max(xplotmax,x[-1])\n", " yplotmax = max(yplotmax,y[-1])" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# calculate the theoretical curve by Langmuir isotherm\n", "Keq = 1.0\n", "f = np.asarray(x)\n", "for i in range(len(x)):\n", " f[i] = Keq * x[i] / (1.0 + Keq * x[i])" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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t8HLBoqon2Ta7fPK0FdDboqjQlKS1/KnAZWb2JJFY7Eusxzi3WDGJlCWzXwP/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\nzMzMrBL/D9Soxgb2EcduAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8,6),dpi=100)\n", "plt.rcParams['xtick.major.size'] = 5\n", "plt.rcParams['xtick.major.width'] = 2\n", "plt.rcParams['xtick.minor.size'] = 3\n", "plt.rcParams['xtick.minor.width'] = 2\n", "plt.rcParams['ytick.major.size'] = 5\n", "plt.rcParams['ytick.major.width'] = 2\n", "plt.rcParams['ytick.minor.size'] = 3\n", "plt.rcParams['ytick.minor.width'] = 2\n", "plt.rcParams['axes.linewidth'] = 2\n", "plt.rcParams['lines.linewidth'] = 2\n", "plt.rcParams['xtick.labelsize'] = 14\n", "plt.rcParams['ytick.labelsize'] = 14\n", "plt.ticklabel_format(axis='y', style='sci', scilimits=(-2,2))\n", "plt.plot(x, f, 'r', linewidth=6)\n", "plt.plot(x, y, 'k', linewidth=3)\n", "plt.xlim(0.0010, 100.0)\n", "plt.ylim(0.0010, 1.0)\n", "plt.xlabel('Concentration of A (mol/cm$^3$)', fontsize=20)\n", "plt.ylabel('Surface converage of A^* (mol/cm$^3$)', fontsize=20)\n", "plt.xscale('log')\n", "plt.yscale('log')\n", "plt.savefig('Langmuir.png')\n", "plt.savefig('Langmuir.ps')\n", "plt.savefig('Langmuir.pdf')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.10" } }, "nbformat": 4, "nbformat_minor": 0 }