Farajvand Mohammad, Kiarostami Vahid, Davallo Mehran, Ghaedi Abdolmohammad
Department of Chemistry, North Tehran Branch, Islamic Azad University, Tehran, Iran.
Department of Chemistry, Gachsaran Branch, Islamic Azad University, Gachsaran, Iran.
Bull Environ Contam Toxicol. 2018 Mar;100(3):402-408. doi: 10.1007/s00128-017-2263-7. Epub 2017 Dec 26.
A multivariate method based on solvent terminated dispersive liquid-liquid microextraction was developed for the determination of Cu ions in aqueous samples. In the proposed approach, di-2-ethylhexylphosphoric acid, xylene and acetone were used as chelating agent, dispersive and extraction solvents, respectively. The effects of various factors on the extraction efficiency such as extraction and dispersive solvent volumes, salt addition and pH were studied using central composite design (CCD) and artificial neural networks coupled bees algorithm (ANN-BA). Upon comparison of these techniques, ANN-BA model was considered to be better optimization method due to its higher percentage relative recovery (about 5%) as compared to the CCD approach. The linear range and the limits of detection (S/N = 3) and quantitation (S/N = 10) were 0.22-140, 0.08 and 0.22 µg L, respectively. Under the optimal conditions, the recoveries for real samples spiked with 0.1 and 0.3 mg L were in the range of 85-98%.
开发了一种基于溶剂终止分散液液微萃取的多元方法，用于测定水样中的铜离子。在所提出的方法中，二（2-乙基己基）磷酸、二甲苯和丙酮分别用作螯合剂、分散剂和萃取剂。使用中心复合设计（CCD）和人工神经网络耦合蜜蜂算法（ANN-BA）研究了各种因素对萃取效率的影响，如萃取剂和分散剂体积、加盐量和pH值。通过比较这些技术，由于ANN-BA模型与CCD方法相比具有更高的相对回收率（约5%），因此被认为是更好的优化方法。线性范围以及检测限（S/N = 3）和定量限（S/N = 10）分别为0.22 - 140、0.08和0.22 μg L。在最佳条件下，加标量为0.1和0.3 mg L的实际样品的回收率在85% - 98%范围内。
