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Diffstat (limited to 'Chemistry/Chapter_13.ipynb')
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diff --git a/Chemistry/Chapter_13.ipynb b/Chemistry/Chapter_13.ipynb new file mode 100755 index 00000000..72db9250 --- /dev/null +++ b/Chemistry/Chapter_13.ipynb @@ -0,0 +1,441 @@ +{
+ "metadata": {
+ "name": ""
+ },
+ "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",
+ "%pylab inline\n",
+ "lnP=numpy.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": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Populating the interactive namespace from numpy and matplotlib\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stderr",
+ "text": [
+ "WARNING: pylab import has clobbered these variables: ['power', 'draw_if_interactive', 'random', 'fft', 'linalg', 'info']\n",
+ "`%pylab --no-import-all` prevents importing * from pylab and numpy\n"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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oKBEBgImJtLP+7FngwQNp4MlvvmEbjIiqTmdbKN26dUNAQABWr15dZvrNmzex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\nbACx9wAAAABJRU5ErkJggg==\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x856d978>"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The rate constant for the decomposition is :2.55e-03 s**-1\n"
+ ]
+ }
+ ],
+ "prompt_number": 76
+ },
+ {
+ "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",
+ "\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",
+ "import numpy\n",
+ "from pylab import *\n",
+ "%pylab 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": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Populating the interactive namespace from numpy and matplotlib\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stderr",
+ "text": [
+ "WARNING: pylab import has clobbered these variables: ['power', 'draw_if_interactive', 'random', 'fft', 'linalg', 'info']\n",
+ "`%pylab --no-import-all` prevents importing * from pylab and numpy\n"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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CdjZMnWoubz9lijlHxcfy9hjnycjIICMjw5LPtmzS4vbt2+nevTuBgYEA5OXl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\ngieeAAAAAElFTkSuQmCC\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x8535d30>"
+ ]
+ },
+ {
+ "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": 80
+ },
+ {
+ "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": {}
+ }
+ ]
+}
\ No newline at end of file |