Journal of Electroanalytical Chemistry, Vol.648, No.2, 176-183, 2010
Prediction of cathode efficiency in electro-deposition of copper-tin using regression and artificial neural network model
The aim of this paper is to develop a model using artificial neural network for the electro-deposition of copper-tin alloy (bronze) based on the experimentally obtained data. The electro-deposition of copper-tin was carried out using an alkaline cyanide bath. Copper and tin contents of coatings were determined using X-ray fluorescence spectroscopy. Cathode efficiencies were determined from the actual and theoretical masses of the deposits. The results were used to create a model for the plating characteristics and also for studies using ANN. The ANN model was compared with the regression model for analysis. (C) 2010 Elsevier B.V. All rights reserved.