Simultaneous immobilization of Dy2O3, graphite and TiO2 to prepare stable nanocomposite for visible light assisted photocatalytic ozonation of a wastewater: Modeling via artificial neural network

Abstract

Abstract In this work, Dy2O3, graphite and TiO2 particles were immobilized simultaneously on the surface of titanium grid sheet using electrophoretic deposition method. The structural and physicochemical properties of the prepared nanocomposite (named as Dy2O3/TiO2/graphite) were studied by XRD, SEM and DRS. Then, photocatalytic ozonation activity of Dy2O3/TiO2/graphite nanocomposite was investigated for decolorization of textile dyeing wastewater. The effect of nanocomposite plate’s number, ozone flow rate, power of applied visible light lamp(s), initial pH and contact time on the decolorization of wastewater was examined. The decolorization efficiency of 90 % was found at ozone flow rate=3 L/min, pH=10, power of visible light=144 W for 90 min using three nanocomposite sheets. Furthermore, an artificial neural network (ANN) model was built to predict the wastewater decolorization process. Findings showed that the ANN could provide good correlation coefficient (R 2 = 0 .99). In addition, the relative effect of each investigated variable on the decolorization of wastewater was assessed. All variables had significant effect on the efficiency of the process. Finally, the reusability study was carried out and results confirmed that Dy2O3/TiO2/graphite kept a good photocatalytic ozonation activity which could be a promising heterogeneous catalyst.