Experimental investigation and mathematical modeling of nano-composite membrane fabrication process: focus on the role of solvent type

In this study, the effect of fabrication parameters on the performance of nano-SiO2-embedded membranes fabricated by three prevalent solvents was investigated. Genetic programming was applied for modeling and estimating the best preparation conditions to obtain a proper membrane for oily wastewater microfiltration. Membranes were prepared via a combination of vapor-induced phase separation and nonsolvent-induced phase separation methods. Different types of solvents such as N-methyl-2-pyrrolidone, N,N-dimethyl formamide, and dimethyl sulfoxide were used in cooperating with SiO2 nanoparticles to improve hydrophilicity properties of polyethersulfone. Thermodynamic behavior of solvents and their interaction with polymer and nonsolvent were considered as criteria for forming a suitable membrane with the maximum effectiveness of nanoparticles. The results showed that nanoparticles are more influential along with a solvent that has a weak affinity with a polymer, which subsequently can produce efficient membranes under conditions with a balance between exposure time and relative humidity. The optimum amounts of parameters were estimated by genetic algorithm to introduce a condition for having a membrane with the maximum permeate flux. Membranes fabricated with dimethyl sulfoxide represented the highest pore size and the most hydrophilic surface, which, in turn, led to the desired membrane (permeate flux 300L/m(2)hr and oil rejection 97%)