Prediction of Photocatalytic Decolorization Acid Red 14 Dye in Aqueous Solutions by UV/NanoTiO2 using Artificial Neural Network Model

Abstract

An artificial neural network model was developed to predict the photocatalytic decolorization of azo dye Acid Red 14 (AR14) in water by a combination of UV/NanoTiO2 system. The initial concentrations of dye, catalyst dosage, pH of the solution and temperature were employed as input to the network; the output of the network was decolorization efficiency. The multilayer feed-forward network was trained by 100 sets of input-output patterns using a back propagation algorithm; a three-layered network with six neurons in the hidden layer gave optimal results. A first order reaction with k= 0.0341 min−1 was observed for the photocatalytic degradation reaction.

Authors and Affiliations

Ali Bodaghi, Reza Moradi

Keywords

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  • EP ID EP19073
  • DOI -
  • Views 268
  • Downloads 9

How To Cite

Ali Bodaghi, Reza Moradi (2014). Prediction of Photocatalytic Decolorization Acid Red 14 Dye in Aqueous Solutions by UV/NanoTiO2 using Artificial Neural Network Model. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(11), -. https://europub.co.uk./articles/-A-19073