%matplotlib inline from matplotlib import pyplot as plt # Variables p_CO2 = [0,25,50,100,200,400,760] ; # Values of partial pressure of CO2 - [mm Hg] y = [0,6.69*10**-2,9.24*10**-2,0.108,0.114,0.127,0.137] ; # adsorption of CO2 -[g adorbed / g seives] # Results plt.plot(p_CO2,y); plt.title('Figure E20.1 The Freundlich and Langmuir iotherms coincide for the adsorption of CO2 on 5A molecular seives'); plt.show()
Populating the interactive namespace from numpy and matplotlib
# Variables G = 1000.0 ; # Volume of solution - [L] S_ad = 1.56 ; # amount of Steptomycin adsorbed per gram resin-[g strep./g resin] cn_S = 6. ; # Concentration of streptomycin solution-[g/L] # Calculations # Assume equilibrium occurs so that total(max) amount of streptomycin is adsorbed max_S = cn_S*G ; # Maximum streptomycin adsorbed-[g] #Use streptomycin balance to get amount of resin required R = max_S/S_ad ; #Amount of resin required to adsorb required amount of streptomycin # Results print 'Amount of resin required to adsorb required amount of streptomycin is %.0f g . '%R
Amount of resin required to adsorb required amount of streptomycin is 3846 g .
# Variables G = 1000. ; # Volume of solution - [L] x = [19.2,17.2,12.6,8.6,3.4,1.4] ; # concentration of solute- [g/L] ac = [0,0.01,0.04,0.08,0.20,0.40] ; # Activated charcoal added-[g/1000g sol] # Assume all concentration can be treated as g solute/1000 g sol. # Calculations y2 = (x-x)/ac ; # -[ g solute/g carbon] y3 = (x-x)/ac ; # -[ g solute/g carbon] y4 = (x-x)/ac ; # -[ g solute/g carbon] y5 = (x-x)/ac ; # -[ g solute/g carbon] y6 = (x-x)/ac ; # -[ g solute/g carbon] # Use polymath to get Freundlich isotherm to bo y= 37.919*x**(0.583) y = 37.919*x**(0.583) ; #From Freundlich isotherm A_by_G = (x-x)/y ; #Minimum mss of activated carbon required- [g carbon/1000 g sol.] # Results print 'Minimum mass of activated carbon required is %.2f g carbon/1000 g sol. '%A_by_G
Minimum mass of activated carbon required is 0.39 g carbon/1000 g sol.