A NEURAL-NETWORK APPROACH TO ZINC AND COPPER INTERFERENCES IN POTENTIOMETRIC STRIPPING ANALYSIS

Zinc and copper are two elements which mutually interfere with each ot her in stripping analysis. The cause is the formation of a Zn-Cu inter metallic compound in the mercury film, which affects both Cu and Zn an alyses. A backward error propagation artificial neural network has bee n applied in a novel approach for the determination of zinc in the pre sence of copper using potentiometric stripping analysis. This performe d well in determining the correct zinc concentration in the sample whe n 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 electrod e). 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.