Abstract
The cationic dye safranin-O was removed from an aqueous solution using the Emulsion Liquid membrane (ELM) method. The ELM system consists of a diluent (hexane) and a surfactant (Span 80). Sulfuric acid (H2SO4) solution was used as an internal aqueous phase. The key parameters regulating the safranin-O dye removal were investigated. Twenty-nine (29) experiments were conducted, with various parameters impacting the removal of the cationic dye safranin-O from aqueous solution using the ELM approach, including surfactant content and internal phase concentration in H2SO4 dye concentration and stirring speed. The RSM with Box–Behnken Design (BBD) was used to optimize and predict the ELM safranin-O cationic dye removal experiments. The model produces 99.68% separated safranin-O in under 2 min of contact time with optimal operation conditions. Furthermore, for forecasting the removal of the cationic dye safranin-O from an aqueous solution by ELM technique, a novel optimization approach based on merging an artificial neural network (ANN) algorithm with a metaheuristic technique, namely PSO, has been proposed. The PSO technique was used to determine the optimal ANN parameter values.
[Display omitted]
•The ELM method was found to be useful in removing the cationic dye safranin-O from an aqueous solution.•The results showed that the safranin-O dye was separated to a maximum of 99.69% after only 2 min of contact time.•ANN-PSO model outperforms the RSM model in predicting percentage of safranin-O removal.