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diff --git a/Chemistry/Chapter_13.ipynb b/Chemistry/Chapter_13.ipynb deleted file mode 100755 index aea83030..00000000 --- a/Chemistry/Chapter_13.ipynb +++ /dev/null @@ -1,412 +0,0 @@ -{ - "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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0Xd/vjqGh4QtueS0trVKi/31/ZL8PI0aMOCF7jFBdXb2yrt/A6tuGy21iYvI8IiJiwPLl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\n54svvvghIiJigEgkkuzfv3+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u4BgKNCe4BDAAAMgF9lAAAEAuUFAAAEAuUFAAAEAuUFAA\nAEAuUFAAAEAuUFAAAEAuUFAAAEAuUFAAAEAu/g+t2fTWyjEZAgAAAABJRU5ErkJggg==\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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\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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