Removal of molybdenum using silver nanoparticles from water samples: Particle swarm optimization-artificial neural network

被引：21

作者：

Khajeh, Mostafa ^{[1
]}

Dastafkan, Kamran ^{[1
]}

机构：

[1] Univ Zabol, Dept Chem, Zabol, Iran

来源：

JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY | 2014年 / 20卷 / 05期

关键词：

Molybdenum; Silver nanoparticles; Artificial neural network; Particle swarm optimization; SPECTROPHOTOMETRIC DETERMINATION; MOLYBDATE ION; ADSORPTION; EXTRACTION; TETRATHIOMOLYBDATE; PRECONCENTRATION; SPECTROMETRY; ELUTION; MO(VI); PYRITE;

D O I：

10.1016/j.jiec.2013.11.036

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

In this study, a simple and fast method for preconcentration and determination of trace amount of molybdenum from water samples was developed by silver nanoparticles based solid-phase extraction method and UV-vis spectrophotometry. Hybrid of artificial neural network-particle swarm optimization (ANN-PSO) has been used to develop predictive models for simulation and optimization of solid phase extraction method. Under the optimum conditions, the detection limit and relative standard deviation were 11 mu g L-1 and <3.9%, respectively. The pre-concentration factor of this method was 50. The method was applied to preconcentration and determination of molybdenum from water samples. (C) 2013 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

引用

页码：3014 / 3018

页数：5

共 29 条

[1] Investigation of removal of Cr(VI), Mo(VI), W(VI), V(IV), and V(V) oxy-ions from industrial waste-waters by adsorption and electrosorption at high-area carbon cloth [J].