Response surface methodology for the modelling of copper removal from aqueous solutions using micellar-enhanced ultrafiltration

Response surface methodology (RSM) was used to study the cumulative effect of the various parameters, namely surfactant (sodium dodecyl sulphate (SDS), anionic) concentration, pH, and surfactant/metal molar ratio and to optimise the process conditions for the maximum removal of copper from aqueous solutions via micellar-enhanced ultrafiltration (MEUF). For obtaining the mutual interaction between the variables and optimising these variables, a central composite design (CCD) by use of response surface methodology was employed. The analysis of variance (ANOVA) of the quadratic model demonstrated that the model was highly significant. The model was statistically tested and verified by experimentation. Values of pH at the range of ca. 7.5 were very successful for the separation. The maximum rejection coefficient of 98.4% was obtained for the following optimal conditions: SDS/Cu2+ molar ratio *r = 7.85, *pH 7.36, *Csurf = 6.82 g/l SDS. A modification of micellar-enhanced ultrafiltration for the removal of copper from aqueous solutions was studied by the implementation of sodium dodecyl sulphate–polyethylene glycol (PEG) aggregates. A full factorial design (FFD) was employed for studying the effect of molar ratio of surfactant/metal, pH and mass ratio of surfactant/polymer at a constant concentration of surfactant equal to 5 g/l. The comparison of the two systems in the region of their common factors showed that the addition of polyethylene glycol caused a slight increase in rejection coefficient of copper but also could function as ‘scavenger’ for surfactant species.