Extraction of nickel using a green emulsion liquid membrane – Process intensification, parameter optimization and artificial neural network modeling

Abstract

This study investigates extraction of nickel from aqueous solution using a green emulsion liquid membrane (GELM). Waste cooking oil and Cyanex 301 showed excellent potential for extraction of nickel as diluent and extractant respectively. Process intensification was achieved through parameter screening and optimization using Plackett Barman design (PBD). Screening of the nine process parameters viz. surfactant concentration (1 - 3, v/v,%), carrier concentration (2-6, v/v,%), agitation speed (200-600, rpm), agitation time (5-15 min), pH of the feed solution (3-7), treat ratio (10-20), internal stripping agent concentration (0.25 – 0.75 M), initial Ni ion concentration (100-500 mg/L) and volume of organic to aqueous phase ratio (1-2), were conducted. Under optimal conditions, the maximum nickel that selectively transferred into the internal phase was 98.7%. The best operating optimum conditions identified were: surfactant concentration – 2.66 (v/v,%), carrier concentration – 5.2 (v/v,%), pH of the feed solution – 4.2, treat ratio – 10.0, initial Ni ion concentration – 100 mg/L. The stripping efficiency and reusability of GELM was also studied for nickel extraction. Artificial neural network (ANN) was employed to model the GELM process and the results were compared.