Litcius/Paper detail

Optimization and prediction of safranin-O cationic dye removal from aqueous solution by emulsion liquid membrane (ELM) using artificial neural network-particle swarm optimization (ANN-PSO) hybrid model and response surface methodology (RSM)

Abdelhalim Fetimi, Attef Dâas, Yacine Benguerba, Slimane Merouani, Mourad Hamachi, Ounissa Kebiche-Senhadji, Oualid Hamdaoui

2021Journal of environmental chemical engineering51 citationsDOI

Topics & Concepts

SafraninCationic polymerizationAqueous solutionBox–Behnken designResponse surface methodologyAqueous two-phase systemChemistryChromatographyMaterials scienceChemical engineeringOrganic chemistryPathologyStainingEngineeringMedicineProcess Optimization and IntegrationExtraction and Separation ProcessesMembrane Separation Technologies
Optimization and prediction of safranin-O cationic dye removal from aqueous solution by emulsion liquid membrane (ELM) using artificial neural network-particle swarm optimization (ANN-PSO) hybrid model and response surface methodology (RSM) | Litcius