Electro oxidation of Malachite Green and Modeling Using ANN

P. A. Soloman, C. Ahmed Basha, M. Velan and N. Balasubramanian

Abstract
This study involves the electro-oxidation of malachite green, a triphenyl methane dye, extensively used in industries and aquaculture, and later banned in most developed countries because of its potential carcinogenicity, mutagenicity and teratogenicity in mammals. The study is conducted in a batch electro-chemical reactor using the catalytic anode (made of noble oxide coated, RuOx-TiOx, titanium expanded mesh) that mediates the oxidation of organic species by the formation of higher oxidation state oxides of the metal (e.g., RuO2 or IrO2). The operating variables are current density, electrolysis time and initial dye concentration. Complete removal of the dye has been reported by 41 minutes of treatment at a current density of 2.2 A dm–2 for the case of initial dye concentration of 200 mg L–1. The experimental data are modeled using back-propagation artificial neural network. The results were compared with experimental observations, and found that the model predictions adequately match experimental observations. Combination of the factors giving complete removal of the dye has also been commented.

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Keywords
Electro-oxidation, malachite green, Artificial Neural Network, modeling