Artificial neural networks study of the catalytic reduction of resazurin: stopped-flow injection kinetic-spectrophotometric determination of Cu(II) and Ni(II)

Abstract

An artificial neural network (ANN) procedure was used in the development of a catalytic spectrophotometric method for the determination of Cu(II) and Ni(II) employing a stopped-flow injection system. The method is based on the catalytic action of these ions on the reduction of resazurin by sulfide. ANNs trained by back-propagation of errors allowed us to model the systems in a concentration range of 0.5–6 and 1–15 mg l −1 for Cu(II) and Ni(II), respectively, with a low relative error of prediction (REP) for each cation: REP Cu(II) = 0.85% and REP Ni(II) = 0.79%. The standard deviations of the repeatability ( s r) and of the within-laboratory reproducibility ( s w) were measured using standard solutions of Cu(II) and Ni(II) equal to 2.75 and 3.5 mg l −1, respectively: s r[Cu(II)] = 0.039 mg l −1, s r[Ni(II)] = 0.044 mg l −1, s w[Ni(II)] = 0.045 mg l −1 and s w[Ni(II)] = 0.050 mg l −1. The ANNs-kinetic method has been applied to the determination of Cu(II) and Ni(II) in electroplating solutions and provided satisfactory results as compared with flame atomic absorption spectrophotometry method. The effect of resazurin, NaOH and Na 2S concentrations and the reaction temperature on the analytical sensitivity is discussed.