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.

这项研究研究了使用绿色乳化液膜（GELM）从水溶液中提取镍。食用废油和Cyanex 301分别具有极好的潜力，可用于萃取镍作为稀释剂和萃取剂。通过使用Plackett Barman设计（PBD）进行参数筛选和优化来实现过程强化。筛选九个工艺参数即。表面活性剂浓度（1-3，v / v，％），载体浓度（2-6，v / v，％），搅拌速度（200-600，rpm），搅拌时间（5-15分钟），进料溶液的pH（3-7），处理比（10-20），内部汽提剂浓度（0.25 – 0.75 M），初始进行镍离子浓度（100-500 mg / L）和有机相与水相的体积比（1-2）。在最佳条件下，选择性转移到内相中的最大镍含量为98.7％。确定的最佳最佳操作条件为：表面活性剂浓度– 2.66（v / v，％），载体浓度– 5.2（v / v，％），进料溶液的pH – 4.2，处理比– 10.0，初始镍离子浓度– 100 mg / L。还研究了GELM的提纯效率和可重复利用性，用于镍的提取。采用人工神经网络（ANN）对GELM过程进行建模，并对结果进行比较。