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{
"metadata": {
"name": "",
"signature": "sha256:160cdac5d7f0b7135dad8dda86f1147a9289b5d9942c1ebb05ca32b461c42f4f"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Chapter 20 : Liquid and Gases in Equilibrium with Solids"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
" Example 20.1 Page no. 594\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"%matplotlib inline\n",
"\n",
"from matplotlib import pyplot as plt\n",
"\n",
"# Variables\n",
"p_CO2 = [0,25,50,100,200,400,760] ;\t\t\t# Values of partial pressure of CO2 - [mm Hg]\n",
"y = [0,6.69*10**-2,9.24*10**-2,0.108,0.114,0.127,0.137] ;\t\t\t# adsorption of CO2 -[g adorbed / g seives]\n",
"\n",
"# Results\n",
"plt.plot(p_CO2,y);\n",
"plt.title('Figure E20.1 The Freundlich and Langmuir iotherms coincide for the adsorption of CO2 on 5A molecular seives');\n",
"plt.show()\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"metadata": {},
"output_type": "display_data",
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HHkF8fLzJuC3N6+GHH8aYMWMQGRmJqKgoxMXFtbrTjxs3Dl26dFH+Xn31Vcye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\nc1U4iFUHtQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1c0f410>"
]
}
],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
" Example 20.2 page no. 596\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"\n",
"# Variables\n",
"G = 1000.0 ;\t\t\t# Volume of solution - [L]\n",
"S_ad = 1.56 ;\t\t\t# amount of Steptomycin adsorbed per gram resin-[g strep./g resin]\n",
"cn_S = 6. ;\t\t\t# Concentration of streptomycin solution-[g/L]\n",
"\n",
"# Calculations\n",
"# Assume equilibrium occurs so that total(max) amount of streptomycin is adsorbed \n",
"max_S = cn_S*G ;\t\t\t# Maximum streptomycin adsorbed-[g]\n",
"#Use streptomycin balance to get amount of resin required \n",
"R = max_S/S_ad ;\t\t\t#Amount of resin required to adsorb required amount of streptomycin\n",
"\n",
"# Results\n",
"print 'Amount of resin required to adsorb required amount of streptomycin is %.0f g . '%R\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Amount of resin required to adsorb required amount of streptomycin is 3846 g . \n"
]
}
],
"prompt_number": 2
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
" Example 20.3 page no. 596\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"# Variables\n",
"G = 1000. ;\t\t\t# Volume of solution - [L]\n",
"x = [19.2,17.2,12.6,8.6,3.4,1.4] ;\t\t\t# concentration of solute- [g/L] \n",
"ac = [0,0.01,0.04,0.08,0.20,0.40] ;\t\t\t# Activated charcoal added-[g/1000g sol] \n",
"# Assume all concentration can be treated as g solute/1000 g sol.\n",
"\n",
"# Calculations\n",
"y2 = (x[0]-x[1])/ac[1] ;\t\t\t# -[ g solute/g carbon]\n",
"y3 = (x[0]-x[2])/ac[2] ;\t\t\t# -[ g solute/g carbon]\n",
"y4 = (x[0]-x[3])/ac[3] ;\t\t\t# -[ g solute/g carbon]\n",
"y5 = (x[0]-x[4])/ac[4] ;\t\t\t# -[ g solute/g carbon]\n",
"y6 = (x[0]-x[5])/ac[5] ;\t\t\t# -[ g solute/g carbon]\n",
"\n",
"# Use polymath to get Freundlich isotherm to bo y= 37.919*x**(0.583)\n",
"y = 37.919*x[5]**(0.583) ;\t\t\t#From Freundlich isotherm\n",
"A_by_G = (x[0]-x[5])/y ;\t\t\t#Minimum mss of activated carbon required- [g carbon/1000 g sol.]\n",
"\n",
"# Results\n",
"print 'Minimum mass of activated carbon required is %.2f g carbon/1000 g sol. '%A_by_G\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Minimum mass of activated carbon required is 0.39 g carbon/1000 g sol. \n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": true,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
|
