supported liquid membrane along with carbon nanotubes and nano graphene oxide for the separation of cu(ii) ions using tributyl phosphate (tbp) as carrier: optimization by d-optimal surface response methodology and artificial neural networks coupled genetic algorithm (ann-ga)

the present study describes s transportation of cu(ii) ions across supported liquid membrane system containing tributyl phosphate (tbp) as carrier which was impregnated on to the teflon supported membrane(ptfe) incorporated with carbon nanotube and nano graphene oxide as sorbent interface. the best organic solvent and the operating conditions of the extraction and stripping for cu(ii) ions has been evaluated by one factor at a time(ofat) method. the influences of several variables, including cu(ii) ions concentration, percentage of tributyl phosphate (as carrier), ph and sulfuric acid concentration were also studied using artificial neural networks-genetic algorithm (annga) and d- optimal response surface methodology to transport of cu(ii) ions from the feed to stripping phase in supported liquid membrane system(slm). comparison of the results achieved using proposed models, showed the ann-ga was better than the rsm model for prediction of transportation of cu(ii) ions using teflon membrane impregnated with tbp with extraction efficiency of 50% and stripping efficiency of 70% with fitness function value of 0.3057. using ann-ga, optimum conditions were set at 25, 2.5, 7 and 1 for cu(ii) ions concentration(ppm), percentage of carrier (%), ph and sulfuric acid concentration(m), respectively. then 0.02 g of carbon nanotubes and nano graphene oxide were added separately and the proposed procedure was carried out. the results showed that with addition of mentioned nano materials, the extraction and stripping efficiency increased to 70 and 69%, respectively, for carbon nanotubes and 65 and 90% for nano grapheme oxide. the present study showed that the developed slm can be applied effectively to extract cu(ii) ions from aqueous solutions.