Visible light photoelectrocatalysis for wastewater treatment using bifacial N-TiO2/Graphene/Ho2O3/Titanium nanocomposite: Artificial neural network modeling and evaluation of ozone addition

Abstract

In this paper, N-TiO2/Graphene/Ho2O3/Titanium bifacial nanocomposite electrode was prepared. First, the effect of Ho2O3 to N-TiO2 wt.% in the nanocomposite preparation matrix was investigated through studying visible light photoelectrocatalysis process in industrial wastewater decolorization. Characterizations of optimum catalyst were performed using DRS, XRD, SEM and EDX analyses. Then, the effect of operating variables i.e. catalyst dosage (electrode number(s)), wastewater pH, applied bias potential, visible light power and contact time on the extent of wastewater decolorization was investigated by the visible light photoelectrocatalysis process. It was observed that almost 80% wastewater decolorization was achieved using the photoelectrocatalysis at the optimum conditions by N-TiO2/Graphene/(10%) Ho2O3. Artificial neural network was used for model the photoelectrocatalysis process and determine the relative importance of investigated operating variables. It was also established that combination of photoelectrocatalysis with ozonation yielded 100% decolorization in 90 min and 96% COD removal in 270 min under the optimized conditions. Moreover, the catalyst sheet was enough stable to be used in all wastewater treatment experiments.