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首页> 外文期刊>Analytica chimica acta >Simultaneous determination of copper, lead and cadmium by cathodic adsorptive stripping voltammetry using artificial neural network
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Simultaneous determination of copper, lead and cadmium by cathodic adsorptive stripping voltammetry using artificial neural network

机译:人工神经网络阴极吸附溶出伏安法同时测定铜,铅和镉

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In this work, simultaneous determination of two groups of elements consisting of Pb(II)-Cd(II) and Cu(II)-Pb(II)-Cd(II) using adsorptive cathodic stripping voltammetry are described. The method is based on accumulation of these metal ions on mercury electrode using xylenol orange as a suitable complexing agent. The potential was scanned to the negative direction and the differential pulse stripping voltammograms were recorded. The instrumental and chemical factors were optimized using artificial neural network. The optimized conditions were obtained in pH of 5.5, xylenol orange concentration of 4.0 mu M, accumulation potential of -0.50 V, accumulation time of 30 s, scan rate of 10 mV/s and pulse height of 70 mV. The relationship between the peak current versus concentration was linear over the range of 5.0-150.0 ng ml(-1) for cadmium and 5.0-150.0 ng ml(-1) for lead. The limits of detection were 0.98 and 1.18 ng ml(-1) for lead and cadmium ions, respectively. In simultaneous determination of Cu(II), Pb(II) and Cd(II) there are inter-metallic interactions, which result a non-linear relationship between the peak current and the ionic concentration for each of the element. Therefore, an artificial neural network was used as the multivariate calibration method. The ANN was constructed with three neurons as the output layer for the simultaneous determination of the three elements. The constructed model was able to predict the concentration of the elements in the ranges of 1.0-50.0, 5.0-200.0 and 10.0-200.0 ng ml(-1), for Cu(H), Pb(H) and Cd(II), respectively. (c) 2006 Elsevier B.V. All rights reserved.
机译:在这项工作中,描述了使用吸附阴极溶出伏安法同时测定由Pb(II)-Cd(II)和Cu(II)-Pb(II)-Cd(II)组成的两组元素。该方法基于使用二甲酚橙作为合适的络合剂在汞电极上累积这些金属离子。将电位扫描到负方向,并记录差分脉冲溶出伏安图。使用人工神经网络优化了仪器和化学因素。在pH 5.5,二甲苯酚橙浓度4.0μM,累积电势-0.50 V,累积时间30 s,扫描速率10 mV / s和脉冲高度70 mV的条件下获得了最佳条件。峰值电流与浓度之间的关系在镉的5.0-150.0 ng ml(-1)和铅的5.0-150.0 ng ml(-1)范围内呈线性关系。铅和镉离子的检出限分别为0.98和1.18 ng ml(-1)。在同时测定Cu(II),Pb(II)和Cd(II)时,存在金属间相互作用,这导致峰值电流与每种元素的离子浓度之间存在非线性关系。因此,人工神经网络被用作多元校准方法。用三个神经元作为输出层构造ANN,以同时确定这三个元素。对于Cu(H),Pb(H)和Cd(II),构建的模型能够预测1.0-50.0、5.0-200.0和10.0-200.0 ng ml(-1)范围内的元素浓度,分别。 (c)2006 Elsevier B.V.保留所有权利。

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