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利用主成分人工神经网络同时分光光度法测定磷酸盐和硅酸盐

Simultaneous spectrophotometric determination of phosphate and silicate by using principal component artificial neural network.

作者信息

Zarei Kobra, Atabati Morteza, Nekoei Mehdi

机构信息

Department of Chemistry, Damghan University of Basic Sciences, Damghan, Iran.

出版信息

Ann Chim. 2007 Aug;97(8):723-31. doi: 10.1002/adic.200790056.

Abstract

A very sensitive, simple and selective spectrophotometric method for simultaneous determination of phosphate and silicate based on formation of phospho- and silicomolybdenum blue complexes in the presence of ascorbic acid is described. Although the complexes of phosphate and silicate with reagent in the presence of ascorbic acid show a spectral overlap, they have been simultaneously determined by principal component artificial neural network (PC-ANN). The PC-ANN architectures were different for phosphate and silicate. The output of phosphate PC-ANN architecture was used as an input for silicate PC-ANN architecture. This modification improves the capability of silicate PC-ANN model for prediction of silicate concentrations. The linear range was 0.01-3.00 microg mL(-1) for phosphate and 0.01-5.00 microg mL(-1) for silicate. Interference effects of common anions and cations were studied and the proposed method was also applied satisfactorily to the determination of phosphate and silicate in detergents.

摘要

描述了一种非常灵敏、简单且具有选择性的分光光度法,用于在抗坏血酸存在下基于磷钼蓝和硅钼蓝配合物的形成同时测定磷酸盐和硅酸盐。尽管在抗坏血酸存在下磷酸盐和硅酸盐与试剂形成的配合物显示出光谱重叠,但它们已通过主成分人工神经网络(PC-ANN)同时测定。磷酸盐和硅酸盐的PC-ANN结构不同。磷酸盐PC-ANN结构的输出用作硅酸盐PC-ANN结构的输入。这种改进提高了硅酸盐PC-ANN模型预测硅酸盐浓度的能力。磷酸盐的线性范围为0.01 - 3.00 μg mL⁻¹,硅酸盐的线性范围为0.01 - 5.00 μg mL⁻¹。研究了常见阴离子和阳离子的干扰效应,该方法也令人满意地应用于洗涤剂中磷酸盐和硅酸盐的测定。

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