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, *C_surf = 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.     

A review on enzyme and ultrasound: A controversial but fruitful relationship

A critical review on the effect of ultrasound (US) on enzymes and their biocatalytic action is presented here. Discussion on the information users of US acquire before utilizing the different devices, and the importance they give to US frequency is constant along the review. The authors have gone into the different areas in which the US–enzyme binomial has been applied. The lack of enough information on the US–enzyme-working conditions under which each piece of research has been developed, and the necessity to provide complete information on the data and metadata to give enough light on each piece of research (and thus on the potential comparison of results from different studies) are critically exposed. With this aim, the study has been divided into the positive effect of US on enzymes to favor the production of metabolites, polymers or proteins; and the degradation, inhibition or activation of the biocatalyst under US application. Also the effect of US on enzyme production and the main fields of application of the US–enzyme binomial are discussed.