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|
{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Chapter 7 : Chemical Kinetics"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"example 7.3 page number 305"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"import math \n",
"\n",
"r = 3**2*3; #according to the rate reaction\n",
"print \"reaction reate will be increased by with 3 times increase in pressure = %f times\"%(r)\n",
"\n",
"r = 3**2*3; #according to the rate reaction\n",
"print \"reaction reate will be increased by with 3 times decrease in volume = %f times\"%(r)\n",
"\n",
"r = 3**2; #according to the rate reaction\n",
"print \"reaction reate will be increased by with 3 times increase in conc of NO = %f times\"%(r)\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"reaction reate will be increased by with 3 times increase in pressure = 27.000000 times\n",
"reaction reate will be increased by with 3 times decrease in volume = 27.000000 times\n",
"reaction reate will be increased by with 3 times increase in conc of NO = 9.000000 times\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"example 7.10 page number 316\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"from scipy.optimize import fsolve \n",
"import math \n",
"moles_A = 3.;\n",
"moles_B = 5.;\n",
"K = 1.;\n",
"\n",
"def F(x):\n",
" return 15.-8*x;\n",
"\n",
"\n",
"x = 10.;\n",
"y = fsolve(F,x)\n",
"\n",
"print \"amount of A transformed = %f percent\"%(y*100/3)\n",
"\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"amount of A transformed = 62.500000 percent\n"
]
}
],
"prompt_number": 2
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"example 7.11 page number 316\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"from scipy.optimize import fsolve \n",
"import math \n",
"Cp = 0.02;\n",
"Cq = 0.02;\n",
"K = 4*10**-2;\n",
"Cb = 0.05;\n",
"Cb_i = Cb+Cp;\n",
"a = (Cp*Cq)/(K*Cb);\n",
"\n",
"def F(x):\n",
" return x-0.02-a;\n",
"\n",
"x = 10.;\n",
"y = fsolve(F,x)\n",
"\n",
"print \"conc of A= %f mol/l\"%(y)\n",
"print \"conc of B= %f mol/l\"%(Cb_i)\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"conc of A= 0.220000 mol/l\n",
"conc of B= 0.070000 mol/l\n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"example 7.12 page number 316\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"import math \n",
"\n",
"Ce_N2 = 3.; #equilibrium conc of N2\n",
"Ce_H2 = 9.; #equilibrium conc of H2\n",
"Ce_NH3 = 4.; #equilibrium conc oh NH3\n",
"\n",
"C_N2 = Ce_N2 + 0.5*Ce_NH3;\n",
"C_H2 = Ce_H2 + 1.5*Ce_NH3;\n",
"\n",
"print \"concentration of N2 = %f mol/l \\nconcentration of H2 = %f mol/l\"%(C_N2,C_H2)\n",
"\n",
"n_H2 = 3.; #stotiometric coefficient\n",
"n_N2 = 1.; #stotiometric coefficient\n",
"n_NH3= 2.; #stotiometric coefficient\n",
"delta_n = n_H2+n_N2-n_NH3;\n",
"if delta_n > 0:\n",
" print \"delta_n =%f since delta_n is greater than 0,equilibrium will shift to right with increase in volume\"%(delta_n)\n",
"\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"concentration of N2 = 5.000000 mol/l \n",
"concentration of H2 = 15.000000 mol/l\n",
"delta_n =2.000000 since delta_n is greater than 0,equilibrium will shift to right with increase in volume\n"
]
}
],
"prompt_number": 5
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"example 7.13 page number 317\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"from scipy.optimize import fsolve \n",
"import math \n",
"moles_A = 0.02;\n",
"K = 1.;\n",
"\n",
"moles_B = 0.02;\n",
"def F(x):\n",
" return moles_A*moles_B-(moles_A+moles_B)*x;\n",
"\n",
"x = 10.;\n",
"y = fsolve(F,x)\n",
"print \"amount of A transformed = %f percent\"%(y*100/0.02)\n",
"\n",
"moles_B = 0.1;\n",
"y = fsolve(F,x)\n",
"print \"amount of A transformed = %f percent\"%(y*100/0.02)\n",
"\n",
"moles_B = 0.2;\n",
"y = fsolve(F,x)\n",
"print \"amount of A transformed = %.0f percent\"%(y*100/0.02)\n",
"\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"amount of A transformed = 50.000000 percent\n",
"amount of A transformed = 83.333333 percent\n",
"amount of A transformed = 91 percent\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"example 7.15 page no : 319\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"import math \n",
"from numpy import *\n",
"from matplotlib.pyplot import *\n",
"\n",
"%pylab inline\n",
"t = array([0,5,10,15,20,25])\n",
"C_A = array([25,18.2,13.2,9.6,7,5.1])\n",
"\n",
"s = 0;\n",
"k = zeros(6)\n",
"\n",
"for i in range(1,6):\n",
" k[i] = (1./t[i])*math.log(25./C_A[i])\n",
" #print (k[i],\"k values for various conc.\")\n",
" s = s+k[i]\n",
"\n",
"print \"average value of k = %f\"%(s/5)\n",
"print (\"ra =- 0.06367*CA\",\"since its a first order reaction,\")\n",
"\n",
"subplot(221) \n",
"plot(t,C_A)\n",
"\n",
"xlabel(\"time\")\n",
"ylabel(\"concentration\")\n",
"suptitle(\"integral method\")\n",
"\n",
"ra = array([1.16,0.83,0.60,0.43])\n",
"C_A = array([18.2,13.2,9.6,7])\n",
"\n",
"subplot(222) \n",
"plot(C_A,ra)\n",
"plot(C_A,ra,'ro')\n",
"xlabel(\"Concentration\")\n",
"ylabel(\"-ra\")\n",
"suptitle(\"differential method\")\n",
"xlim(1,20)\n",
"ylim(.1,2)\n",
"print \"rate from differential method = -0.064*CA\"\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n",
"average value of k = 0.063680\n",
"('ra =- 0.06367*CA', 'since its a first order reaction,')\n",
"rate from differential method = -0.064*CA"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"WARNING: pylab import has clobbered these variables: ['draw_if_interactive', 'new_figure_manager']\n",
"`%pylab --no-import-all` prevents importing * from pylab and numpy\n"
]
},
{
"metadata": {},
"output_type": "display_data",
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ER0cjPz+/3n6m2N/1229i3dm4EXjiCWDbNiAkROqoTJ82+rpUpo3z589TREQE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\n6kMaAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x2b3a490>"
]
}
],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"example 7.16 page no : 322\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"import math \n",
"E = 75200. #in J/mol\n",
"E1 = 50100. #in J/mol\n",
"R = 8.314 #in J/mol K\n",
"T = 298. #in K\n",
"\n",
"ratio = math.exp((E1-E)/(R*T));\n",
"rate_increase = ratio**-1\n",
"\n",
"print \"increase in rate of reaction =\",rate_increase,\"times\"\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"increase in rate of reaction = 25106.6042072 times\n"
]
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
|
