DECOLORIZATION OF BINARY DYE MIXTURE BY ELECTROCOAGULATION AND MODELING OF EXPERIMENTAL RESULTS USING ARTIFICIAL NEURAL NETWORK

Abstract

Electrocoagulation (EC) is one of the widely used methods for the removal of dye pollutants from dye contaminated effluents. In this study, removal of binary dye mixtures from aqueous solution was carried out by direct current electrocoagulation. The effect of the operating parameters such as current density, electrolyte concentration, dyestuff concentration and pH of solution on decolorization of aqueous solution containing both Direct Blue 86 (DB86) and Reactive Yellow 145 (RY145) were studied. In the presence of both dyes, the optimum current density, time of electrolysis and initial pH of the dye solution were found to be 10.53 A/m(2), 10 min and 4, respectively. NaCl electrolyte was found to be the best suited electrolyte for the electrocoagulation process. Under the optimized conditions in the presence of 100 mgL(-1) from each dyes, the color removal efficiency was reached 98.75% for DB86 and 95.05% for RY145. An artificial neural networks (ANN) model was developed to predict the performance of decolorization efficiency by EC process. A comparison between the predicted results of the designed ANN model and experimental data was also performed. A comparison between the model results and experimental data gave high correlation coefficients (0.9907 for DB86, 0.9763 for RY145 and 0.9947 for DB86 and RY145).