Simultaneous Spectrophotometric Determination of Phosphate and Silicate by Using Principal Component Artificial Neural Network

Kobra Zarei, Morteza Atabati, Mehdi Nekoei
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引用次数: 3

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 μg mL-1 for phosphate and 0.01-5.00 μg 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.

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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
介绍了一种非常灵敏、简便、选择性的同时测定磷酸盐和硅酸盐的分光光度法,该方法基于在抗坏血酸存在下形成的磷和硅钼蓝配合物。虽然在抗坏血酸存在的情况下,磷酸盐和硅酸盐与试剂的配合物表现出光谱重叠,但它们已被主成分人工神经网络(PC-ANN)同时确定。对于磷酸盐和硅酸盐,PC-ANN结构是不同的。磷酸盐PC-ANN结构的输出被用作硅酸盐PC-ANN结构的输入。这一改进提高了硅酸盐PC-ANN模型预测硅酸盐浓度的能力。磷酸盐在0.01 ~ 3.00 μg mL-1范围内,硅酸盐在0.01 ~ 5.00 μg mL-1范围内呈线性关系。研究了常见阴离子和阳离子的干扰作用,并将该方法应用于洗涤剂中磷酸盐和硅酸盐的测定。
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