Photocatalytic Treatment of Binary Mixture of Dyes using UV/TiO2 Process: Calibration, Modeling, Optimization and Mineralization Study

Abstract

Abstract Photocatalytic treatment of a binary dye mixture (Acid Blue 113 (AB113) and Acid Red 114 (AR114)) has been done in a slurry pond reactor using TiO2 as a photocatalyst with UV light irradiation (UV-C). Two different methods, namely multivariate calibration and first order derivative spectrophotometric were used to quantify each dye separately in binary dye solutions. The behavior of the photocatalytic degradation of a binary dye mixture was predicted using an artificial neural network (ANN) model. Five process parameters (initial concentration of AB113 dye, initial concentration of AR114 dye, TiO2 dose, initial pH of the dye mixture and time were used as inputs and decolorization efficiency of AB113 and AR114 were used as output of the ANN. The parametric optimization has been done by the multi-response optimization with desirability function methodology. Optimization by Central Composite Design (CCD) effectively handles the relations among optimizing process variables and its prediction concurred well with the experimental run and artificial neural network (ANN) model. The reaction kinetic rates of decolorization of both dyes (AB113 and AR114) were found to be first order. Total organic carbon (TOC) removal and possible reaction pathway show the total mineralization of both dyes in binary dye mixture.