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diff --git a/Chemistry/Chapter_13.ipynb b/Chemistry/Chapter_13.ipynb new file mode 100755 index 00000000..aea83030 --- /dev/null +++ b/Chemistry/Chapter_13.ipynb @@ -0,0 +1,412 @@ +{ + "metadata": { + "name": "", + "signature": "sha256:895c072b6753209785681491473fcfce8d9e8b03552e6c5bac0de19645eb5d94" + }, + "nbformat": 3, + "nbformat_minor": 0, + "worksheets": [ + { + "cells": [ + { + "cell_type": "heading", + "level": 1, + "metadata": {}, + "source": [ + "Chapter 13:Chemical Kinetics" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example no:13.2,Page no:564" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Variable declaration\n", + "dO2=-0.024 #rate of reaction of O2, M/s\n", + "\n", + "#Calculation\n", + "#(a)\n", + "dN2O5=-2*dO2 #rate of formation of N2O5, M/s\n", + "#(b)\n", + "dNO2=4*dO2 #rate of reaction of NO2, M/s\n", + "\n", + "#Result\n", + "print\"(a).The rate of formation of N2O5 is :\",dN2O5,\"M/s\"\n", + "print\"(b).The rate of reaction of NO2 is :\",dNO2,\"M/s\"\n" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "(a).The rate of formation of N2O5 is : 0.048 M/s\n", + "(b).The rate of reaction of NO2 is : -0.096 M/s\n" + ] + } + ], + "prompt_number": 2 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example no:13.3,Page no:568" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Variable declaration\n", + "NO1=5*10**-3 #conc of NO from 1st experiment, M\n", + "H21=2*10**-3 #conc of H2 from 1st experiment, M\n", + "r1=1.3*10**-5 #initial rate from 1st experiment, M/s\n", + "NO2=10*10**-3 #conc of NO from 2nd experiment, M\n", + "H22=2*10**-3 #conc of H2 from 2nd experiment, M\n", + "r2=5*10**-5 #initial rate from 1st experiment, M/s\n", + "NO3=10*10**-3 #conc of NO from 3rd experiment, M\n", + "H23=4*10**-3 #conc of H2 from 3rd experiment, M\n", + "r3=10*10**-5 #initial rate from 3rd experiment, M/s\n", + "\n", + "#Calculation\n", + "import math\n", + "#(a)\n", + "#r=k*NO**x*H2**y, dividing r2/r1 and r3/r2\n", + "x=math.log(r2/r1)/math.log(NO2/NO1) #since H21=H22\n", + "y=math.log(r3/r2)/math.log(H23/H22) #since NO3=NO2\n", + "x=round(x) \n", + "y=round(y) \n", + "#(b)\n", + "k=r2/((NO2)**x*H22**y) #rate constant, /M**2 s\n", + "#(c)\n", + "NO=12*10**-3 #conc of NO, M\n", + "H2=6*10**-3 #conc of H2, M\n", + "rate=k*(NO**x)*H2**y #rate, M/s\n", + "\n", + "#Result\n", + "print\"(a) the rate of reaction is : r=k[NO]**\",x,\"*[H2]**\",y\n", + "print\"(b) the rate constant of the reaction is :%.1e\"%k,\" /M**2 s\" \n", + "print\"(c) the rate of reaction at given concentration is :%.1e\"%rate,\" M/s\"\n" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "(a) the rate of reaction is : r=k[NO]** 2.0 *[H2]** 1.0\n", + "(b) the rate constant of the reaction is :2.5e+02 /M**2 s\n", + "(c) the rate of reaction at given concentration is :2.2e-04 M/s\n" + ] + } + ], + "prompt_number": 72 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example no:13.4,Page no:571" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Variable declaration\n", + "t=8.8*60 #time, s\n", + "k=6.7*10**-4 #rate constant, s-1\n", + "\n", + "#Calculation\n", + "import math\n", + "#(a)\n", + "Ao1=0.25 #initial conc, M\n", + "A1=math.exp(-k*t+math.log(Ao1)) #final conc, M\n", + "#(b)\n", + "A2=0.15 #initial conc, M\n", + "Ao2=0.25 #final conc, M\n", + "t2=-math.log(A2/Ao2)/(60*k) #time, min\n", + "#(c)\n", + "percent=74.0 \n", + "#let initial conc be 1\n", + "Ao3=1.0 #initial conc, M\n", + "A3=1.0-percent/100.0 #final conc, M\n", + "t3=-math.log(A3/Ao3)/(k*60.0) #time, min\n", + "print\"(a) the concentration of cyclopropane at given time is :\",round(A1,2),\"M\"\n", + "print\"(b) the time required is :\",round(t2),\"min\"\n", + "print\"(c) the time required for required conversion is :%.1f\"%t3,\"min(approx)\"" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "(a) the concentration of cyclopropane at given time is : 0.18 M\n", + "(b) the time required is : 13.0 min\n", + "(c) the time required for required conversion is :33.5 min(approx)\n" + ] + } + ], + "prompt_number": 75 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example no:13.5,Page no:573" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Variable declaration\n", + "t=[0,100,150,200,250,300] #time(data given), s\n", + "P=[284.0,220.0,193.0,170.0,150.0,132.0] #pressure(data given) in mmHg corresponding to time values\n", + "lnP=[0,0,0,0,0,0]\n", + "\n", + "#Calculation\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from pylab import *\n", + "%matplotlib inline\n", + "lnP=np.log(P) #lnP values corresponding to P\n", + "A=plot(t,lnP)\n", + "plt.xlim(0,350)\n", + "plt.ylim(4.8,5.8)\n", + "plt.ylabel('$ln Pt$')\n", + "plt.xlabel('$t(s)$')\n", + "plt.title('Plot of ln Pt versus time for the decomposition of azomethane\\n')\n", + "slope=np.polyfit(t,lnP,1)\n", + "k=-slope[0]\n", + "\n", + "#Result\n", + "show(A)\n", + "print\"The rate constant for the decomposition is :%.2e\"%k,\"s**-1\"\n" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": 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yvlMBQHOEgtIEaGoSLV3KDpF/9y57tv3p03ynAoDmBk1eTVBkJHu2fbt2RNu2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\n", + "text": [ + "<matplotlib.figure.Figure at 0x3f0c650>" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "The rate constant for the decomposition is :2.55e-03 s**-1\n" + ] + } + ], + "prompt_number": 2 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example no:13.6,Page no:576" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Variable declaration\n", + "k=5.36*10**-4 #rate constant, s-1\n", + "\n", + "#Calculation\n", + "t_half=0.693/(60*k) #half life of the reaction, min\n", + "\n", + "#Result\n", + "print\"The half life for the decomposition of ethane is :\",round(t_half,1),\"min\"" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "The half life for the decomposition of ethane is : 21.5 min\n" + ] + } + ], + "prompt_number": 77 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example no:13.7,Page no:578" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Variable declaration\n", + "k=7*10**9 #rate constant, M s\n", + "\n", + "#Calculation\n", + "#(a)\n", + "t=2*60 #half life of the reaction, s\n", + "Ao1=0.086 \n", + "A1=(k*t+1/Ao1)**-1 \n", + "#(b)\n", + "Ao2=0.6 \n", + "t_half2=1/(Ao2*k) #half life of the reaction, s\n", + "Ao3=0.42 \n", + "t_half3=1/(Ao3*k) #half life of the reaction, s\n", + "\n", + "#Result\n", + "print\"(a.)The concentration of I is :%.1e\"%A1,\"M\"\n", + "print\"(b.)The half life for Io=0.6 is :%.1e\"%t_half2,\"s\"\n", + "print\" The half life for Io=0.42 is :%.1e\"%t_half3,\"s\"" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "(a.)The concentration of I is :1.2e-12 M\n", + "(b.)The half life for Io=0.6 is :2.4e-10 s\n", + " The half life for Io=0.42 is :3.4e-10 s\n" + ] + } + ], + "prompt_number": 79 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example no:13.8,Page no:584" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Variable declaration\n", + "T=[700.0,730.0,760.0,790.0,810.0] #temperature(data given), K\n", + "R=8.314 #gas constant, kJ/mol\n", + "k=[0.011,0.035,0.105,0.343,0.789] #rate constant(data given) in 1/M**1/2 s corresponding to temperature values\n", + "import numpy\n", + "#Calculation\n", + "x=numpy.reciprocal(T) #1/T values corresponding to Temp values above, K-1\n", + "x=numpy.round(x,5)\n", + "import math\n", + "\n", + "from pylab import *\n", + "%matplotlib inline\n", + "lnk=numpy.log(k) #lnk values corresponding to k\n", + "lnk[0]=numpy.round(lnk[0],2)\n", + "lnk[1]=numpy.round(lnk[1],2)\n", + "lnk[2]=numpy.round(lnk[2],3)\n", + "lnk[3]=numpy.round(lnk[3],3)\n", + "lnk[4]=numpy.round(lnk[4],3)\n", + "A=plot(x,lnk,marker='o', linestyle='-')\n", + "plt.xlim(1.2*10**-3,1.45*10**-3)\n", + "plt.ylim(-5.0,0.0)\n", + "plt.ylabel('$ln k$')\n", + "plt.xlabel('$1/T(K^-1)$')\n", + "plt.title('Plot of ln k versus 1/T\\n')\n", + "slope=np.polyfit(x,lnk,1)\n", + "Ea=-slope[0]*R #activation energy, kJ/mol\n", + "\n", + "#Result\n", + "show(A)\n", + "print\"The activation energy for the decomposition is :%.3e\"%(Ea/1000),\"kJ/mol\"\n", + "print\"NOTE:Slope is approximately calculated in book,that's why wrong answer\"" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": 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dXESkFbZsAaZNA4YNAz79FLCyEjsi3cZuLiIySMOHCxVKcbEw2TE+XuyIqD5Y\nmRCR1jlwAHjzTaB7d2D5cqBlS7Ej0j2sTIjI4PXpIywc2bq18KTXxo2c7KjtWJkQkVZLSgLeeANw\ndARWrQLatRM7It3AyoSIqBp/fyA5GejZE/D1BVauBKqqxI6KamJlQkQ64+JFoUpRKISdHTt3Fjsi\n7cXKhIjoEdzdgcRE4JVXgKAg4JNPgLIysaMigMmEiHSMkRHw9tvA6dPCWl++voBcLnZUxGRCRDqp\nbVvgt9+AOXOEDblmzhTW+iJxaEUyWbp06SwjI6Oq27dvNxc7FiLSHRIJMHq0sLPjX38JjxHv3y92\nVIZJ9GSSlZXVdt++fcFPPfXUn2LHQkS6yc4O2LAB+PprYc+UCROA27fFjsqwiJ5MZs6cuWzx4sWz\nxY6DiHRfaKhQpVhZCUuybN7MyY6aYiLmh2/fvv1FJyenbE9Pz7OPOy88PPzhn2UyGWQymZojIyJd\nZWUFrFghdH9NnCjMnv/6a2HSoz5LSEhAQkKCaJ+v9nkmwcHB+/Ly8hxqHo+MjJy7aNGiOXv37u3X\nrFmze+3bt7+WnJzs16JFi7//FSDnmRBRA5WWAosWAd98A0RGCnNUjETvj9EMTc8zEW3S4vnz57v0\n6dPngIWFRREAZGdnOzk6OubI5fKAVq1a3XoYIJMJEano/HmhSjE3B1avBlxdxY5I/QwmmdTUvn37\na6dOnfJt3rz5v4bNmEyIqDFUVgJRUUBEBPDee8KjxKamYkelPgY7A14ikTBjEJHaGBsDM2YIC0ce\nOAAEBgoTH6lxaE1l8iisTIiosSkUwPr1wOzZwmPECxcKXWD6xGArEyIiTZFIgPHjhT1Trl0DvLyA\nw4fFjkq3sTIhIoO3YwcwZQowYACweDFgbS12RKpjZUJEpGGDBwtPfBkZAR4ewPbtYkeke1iZEBFV\nc/gwMGmS0PUVFQU4/GeWnG5gZUJEJKJevYDUVKBjRyGh/Pgjl2SpC1YmRESPkJIizJpv0QKIjgba\ntxc7orpjZUJEpCV8fIQNuIKDgYAA4MsvhcmP9F+sTIiI6uDKFWEs5cEDYM0aYe8UbcbKhIhIC3Xs\nCBw8KCSU558H5s8XFpIkAZMJEVEdSSRCMklNFR4l9vEBjh0TOyrtwG4uIqIGUCiArVuBsDBg2DBh\nqXsrK7Gj+ge7uYiIdIBEAgwfLlQoRUXCzo7x8WJHJR5WJkREjeDAAeDNN4Hu3YHly4GWLcWNh5UJ\nEZEO6tN6eCHgAAALeklEQVRHWDjSwUF40mvjRsOa7MjKhIiokSUlCZMdnZyAb78Fzp1LxIoVe1Fa\nagKptAJhYf0wcGCQWmPQdGVioqkPIiIyFP7+QHKysAJxly6JkEr3ID8/8uH7GRlzAUDtCUWTWJkQ\nEanRs8/Ow9GjEf853r//fOze/YnaPpdjJkREesTEpPYOoJISYw1Hol5MJkREaiSVVtR63MxMvxb5\nYjIhIlKjsLB+cHGZ+69jLi5zMG1asEgRqQfHTIiI1CwuLhFRUftQUmIMM7NKTJsWrHdPczGZEBHp\nIQ7AExGRzmEyISIilTGZEBGRyphMiIhIZUwmRESkMiYTIiJSGZMJERGpjMmEiIhUxmRCREQqYzIh\nIiKVMZkQEZHKmEyIiEhlTCZERKQyJhMdkpCQIHYIWoNt8Q+2xT/YFuIRNZmEh4eHOzk5Zfv4+KT4\n+Pik7N69O0TMeLQd/0f5B9viH2yLf7AtxFP75sQaIpFIFDNnzlw2c+bMZWLGQUREqhG9m0uTm7cQ\nEZF6iLrT4kcffbRw7dq1E6ytre/6+fklL126dJaNjc2d6udIJBJus0hE1AB6tW1vcHDwvry8PIea\nxyMjI+d27979RMuWLf8CgPnz53+Sm5vbes2aNRPVGhARETU6rdkDPjMz03nQoEG/nTt3rqvYsRAR\nUf2IOmaSm5vbWvnn2NjYoV27dj0nZjxERNQwolYm48aNW3/mzBlviUSiaN++/bXo6OjJ9vb2N0UL\niIiIGkRtlcnu3btD3N3dL7q6ul7+/PPP36/tHBsbmzvFxcXmALBw4cKPlInkUddu3rx5hIeHR5qx\nsXHlqVOnfJXH9+3bF+zn55fs6el51s/PL/nQoUO9le+dOnXKt2vXrudcXV0vT58+/St1fd/HqUtb\nhIWFrXB1db3s5eWVmpKS4vOkaxvSFjKZLMHd3f2icl5Pfn6+nbq+86Oouy1Onz7dTXlcLpcHKL+r\np6fn2Z9//vll5XuGcF/UtS3Evi802Q5K169fb2dpaVm4dOnSWcpj2nBPANrTHvW+LxQKRaO/Kioq\njF1cXK5cu3bNuayszNTLy+vMH3/80bn6OXFxcQNCQ0PjFQoFTpw4ERgYGHjiSddeuHDBPT093U0m\nkx06depUN+XvSklJ8c7NzXVQKBQ4f/68h6OjY7byPX9/f/nJkycDFAoFQkND43ft2hWiju+sC21R\n81xNvzTdFkVFReaVlZVGCoUCubm5Di1atMivqKgwNsT74nFtIeZ9oel2UL6GDx/+68iRI39esmTJ\nLOUxse8JbWuP+t4XaqlM5HJ5QMeOHa84Oztnmpqalo8aNWrT9u3bX6x+zo4dOwaPHz9+HQAEBgae\nvHPnjk1eXp7D4651d3e/6Obmdqnm53l7e59xcHDIA4Cnn376j+LiYvPy8nLT3Nzc1vfv37cKCAiQ\nA0K32rZt24ao4zs/ira0hfJ9hYjzejTdFubm5sVGRkZVAFBcXGxubW1919jYuNIQ74tHtYXyfbHu\nC023AwBs27ZtSIcOHa4+/fTTfyiPacM9AWhPeyjV575QSzLJyclxbNu2bZbyZycnp+ycnBzHupxz\n48aNNk+69nG2bNky3NfX95SpqWl5Tk6Oo5OTU7byPUdHx5z6/K7GoC1toTw2fvz4dT4+PikRERHz\nGv6tGkaMtpDL5QEeHh5pHh4eacuWLZup/AxDvC9qawslse4LTbdDYWGh5eLFi2eHh4eH1/wMse8J\nZRza0B5K9bkv1JJM6jrRsLH/NZSWlubxwQcffBYdHT25MX+vKrSpLTZu3PjK+fPnuxw5cuS5I0eO\nPLdhw4axjfmZTyJGWwQEBMjT0tI8Tp8+3W369Olf3b1717qxfrcqtKktxLwvNN0O4eHh4e+8886X\nFhYWRWJW6Y+iTe1R3/tCLWtzOTo65mRlZbVV/pyVldW2etav7Zzs7GwnJyen7PLyctMnXVub7Oxs\np2HDhm3dsGHD2Pbt219TfkZ2drZT9XMcHR1zVP1+9aEtbQEAbdq0uQEAlpaWhWPGjPlJLpcHjB07\ndoOq37GuxGgLJXd394suLi4ZV65c6ejk5JRtiPeFUvW28PX1PSXmfaHpdpDL5QFbtmwZPnv27MV3\n7tyxMTIyqjI3Ny8eNmzYVrHvCUB72uPtt9/+pt73hToGkcrLy006dOiQce3aNefS0tImTxpEOn78\neHflIFJdrpXJZIeSk5N9lT8XFBTYeHp6psbGxg6pGUtAQMDJEydOBFZVVUnEGFTTlraoqKgw/uuv\nv+wUCgXKyspMhw8f/mt0dPSb+twW165dcy4vLzdRKBTIzMx8qm3bttfv3r3bzBDvi0e1hdj3habb\noforPDx84dKlS2cqfxb7ntCm9mjIfaG2RomPjw91c3NLd3FxubJo0aIPFQoFVq1aNXnVqlWTledM\nmTJlpYuLyxVPT8/U6k8N1HatQqHA1q1bhzo5OWWZmZkV29vb54WEhOxSKBT45JNP5jVt2rTQ29s7\nRflSNkRycrJvly5dzrm4uFyZNm3aCk3fHNrSFoWFhU19fX2TPT09Uz08PM7PmDHjy6qqKok+t8X6\n9evHenh4nPf29k7x9/eXV//LwdDui0e1hTbcF5psh+qvmslEG+4JbWmPhtwXWrOcChER6S7Rl6An\nIiLdx2RCREQqYzIhIiKVMZkQEZHKmEyIiEhlTCZERKQyJhMyeBUVFSbp6emdnnReaWmpVJ1xlJSU\nmKnz9xOpE5MJGYSqqiqjmTNnLqvtvYSEBJmRkVHVpUuX3EJDQ3dFR0dP7tu37/6JEyeuiY6Onuzr\n63tq586dL9y/f99Kec2SJUvebd26da5yvaLs7Gynzp07X1i1atX/bty40WbPnj39la/jx48/U5eY\nsrOznfbv39+3sb87kSaoZW0uIm1SUFBgu3bt2gmHDx/uVdv76enpnfr27bv/l19+Gbljx47Bpqam\n5bGxsUNnz569uFOnTunW1tZ3792718zOzi5feY2fn19ySEjI7rFjx26oqqoyOnbsWI+TJ08GNmvW\n7B7wzzpo9YmpY8eOV+Lj4wf07NnzqLm5eXFjfX8iTWBlQnrP1ta2YObMmcuUf9HXpNznw9XV9bJy\nuf5Lly65derUKR0Arl692mHo0KGx1a85efJkYGBg4MnS0lLpL7/8MnLIkCHbHvX76xPTwIED42Ji\nYkbX9zsSiY3JhAyaXC4P8Pf3TwIAHx+fFAC4fPmyq4uLS4bynFu3brWqWSkkJSX5u7m5XXrppZd+\ndXNzu9SkSZOyxojHxcUl49y5c10b43cRaRKTCRm0U6dO+fr5+SVXPyaXywOUO+4BtQ+MJyUl+f/9\n998tBg8evGPjxo2vNGZMFRUV7H4mncNkQgatqqrqP/8PJCUl+Xfv3v2E8ufq2x4DQF5enkPr1q1z\nR4wYsXnEiBGbt23bNkTRiBstFRUVWTTW7yLSFCYTMljp6emdlOMi1SUlJfkru74AoPpe6YAwXqJM\nNjY2Nnf8/f2T9u3bF9xYcSnHcIh0CZMJ6b0HDx40/fLLL9+5cOFC5+XLl8948OBBU0B4JFgmkyUo\nz0tNTfX64osv3jt79qxnbGzs0Fu3brUCAAsLiyLlOceOHevxzTffvJ2Xl+eQk5PjWFRUZFFUVGSx\ncOHCjy5duuSmakwKhUJiZWV1v9G+PJGGcD8TMlhRUVHTpk2bFvWk85YsWfLuxIkT19ja2haoO6bU\n1FSvixcvur/88ss/q/uziBoTKxMySDdu3GhT1z2+J02atHrz5s0j1B0TABw4cKDPiBEjNmvis4ga\nE5MJGaQjR448179//z11Odfa2vpu586dL1y/fr2dOmNKS0vz6NOnzwGOmZAuYjcXERGpjJUJERGp\njMmEiIhUxmRCREQqYzIhIiKVMZkQEZHKmEyIiEhlTCZERKQyJhMiIlLZ/wMBDhqhMGwlewAAAABJ\nRU5ErkJggg==\n", + "text": [ + "<matplotlib.figure.Figure at 0x3f9ffd0>" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "The activation energy for the decomposition is :1.797e+02 kJ/mol\n", + "NOTE:Slope is approximately calculated in book,that's why wrong answer\n" + ] + } + ], + "prompt_number": 4 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example no:13.9,Page no:586" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import math\n", + "#Variable declaration\n", + "k1=3.46*10**-2 #rate constant at T1\n", + "T1=298 #temp K\n", + "T2=350 #temp K\n", + "R=8.314 #gas constant,J/K mol\n", + "Ea=50.2*1000 #activation energy, J/mol\n", + "\n", + "#Calculation\n", + "k2=k1/math.exp(Ea/R*(T1-T2)/(T1*T2)) #from equation ln(k1/k2)=Ea*(T1-T2)/(T1*T2*R), S-1\n", + "\n", + "#Result\n", + "print\"The rate constant at temp 350 is :\",round(k2,3),\"s**-1\"" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "The rate constant at temp 350 is : 0.702 s**-1\n" + ] + } + ], + "prompt_number": 81 + } + ], + "metadata": {} + } + ] +}
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