Department of Chemistry, North Tehran Branch, Islamic Azad University, Tehran, Iran.
Department of Chemistry, Gachsaran Branch, Islamic Azad University, Gachsaran, Iran.
Environ Monit Assess. 2019 Apr 17;191(5):287. doi: 10.1007/s10661-019-7383-6.
Solvent-terminated dispersive liquid-liquid microextraction (ST-DLLME) as a simple, fast, and low-cost technique was developed for simultaneous extraction of Cd and Cu ions in aqueous solutions. Multiobjective evolutionary algorithm based on decomposition with the aid of artificial neural networks (ANN-MOEA/D) was used for the first time in chemistry, environment, and food sciences to optimize several independent variables affecting the extraction efficiency, including disperser volume and extraction solvent volume, pH, and salt addition. To perform the ST-DLLME operations, xylene, methanol, and dithizone were utilized as an extraction solvent, disperser solvent, and chelating agent, respectively. Non-dominated sorting genetic algorithm versions II and III (NSGA II and NSGA III) as multiobjective metaheuristic algorithms and in addition central composite design (CCD) were studied as comparable optimization methods. A comparison of results from these techniques revealed that ANN-MOEA/D model was the best optimization technique owing to its highest efficiency (97.6% for Cd and 98.3% for Cu). Under optimal conditions obtained by ANN-MOEAD, the detection limit (S/N = 3), the quantitation limit(S/N = 10), and the linear range for Cu were 0.05, 0.15, and 0.15-1000 μg L, respectively, and for Cd were 0.07, 0.21, and 0.21-750 μg L, respectively. The real sample recoveries at a spiking level of 0.05, 0.1, and 0.3 mg L of Cu and Cd ions under the optimal conditions obtained by ANN-MOEA/D ranged from 94.8 to 105%.
溶剂终止分散液液微萃取（ST-DLLME）作为一种简单、快速、低成本的技术，被开发用于同时萃取水溶液中的 Cd 和 Cu 离子。基于分解的多目标进化算法（ANN-MOEA/D）首次应用于化学、环境和食品科学领域，用于优化影响萃取效率的多个独立变量，包括分散剂体积和萃取溶剂体积、pH 值和加盐量。为了进行 ST-DLLME 操作，二甲苯、甲醇和二硫腙分别用作萃取溶剂、分散剂溶剂和螯合剂。非支配排序遗传算法版本 II 和 III（NSGA II 和 NSGA III）作为多目标元启发式算法，以及中心复合设计（CCD）作为可比的优化方法进行了研究。对这些技术的结果进行比较表明，由于其最高效率（Cd 为 97.6%，Cu 为 98.3%），ANN-MOEA/D 模型是最佳的优化技术。在 ANN-MOEAD 获得的最佳条件下，Cu 的检测限（S/N=3）、定量限（S/N=10）和线性范围分别为 0.05、0.15 和 0.15-1000μg/L，而 Cd 的检测限分别为 0.07、0.21 和 0.21-750μg/L。在通过 ANN-MOEA/D 获得的最佳条件下，在 0.05、0.1 和 0.3mg/L 的 Cu 和 Cd 离子的加标水平下，实际样品的回收率在 94.8%至 105%之间。
