A Neural Network Approach to Zinc and Copper Interferences in Potentiometric Stripping Analysis

Zinc and copper are two elements which mutually interfere with each other in stripping analysis. The cause is the formation of a Zn-Cu intermetallic compound in the mercury film, which affects both Cu and Zn analyses. A backward error propagation artificial neural network has been applied in a novel...

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Veröffentlicht in:Journal of intelligent material systems and structures 1997-02, Vol.8 (2), p.177-183
Hauptverfasser: Chow, Christopher W. K., Davey, David E., Mulcahy, Dennis E.
Format: Artikel
Sprache:eng
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Zusammenfassung:Zinc and copper are two elements which mutually interfere with each other in stripping analysis. The cause is the formation of a Zn-Cu intermetallic compound in the mercury film, which affects both Cu and Zn analyses. A backward error propagation artificial neural network has been applied in a novel approach for the determination of zinc in the presence of copper using potentiometric stripping analysis. This performed well in determining the correct zinc concentration in the sample when provided with the stripping times of zinc and copper and the copper concentration (determined by shifting the plating potential to a lower value to prevent the zinc being plated onto the mercury film electrode). The unknown zinc concentration was determined following an initial period of network exposure to a set of experimental data, which were used as examples of the required input/output data mapping.
ISSN:1045-389X
1530-8138
DOI:10.1177/1045389X9700800208