Investigation of continuous sono-photocatalytic membrane reactor in degradation of organic pollutant: Artificial neural network modeling

In this work, the degradation of Reactive Orange 29 was studied using submerged sono-photocatalytic membrane reactor (SPMR) combining N-TiO2 nanoparticles, visible light lamp(s) and polyvinylidene fluoride (PVDF) membrane. Modeling of experimental results by artificial neural network was done. The effect of operational variables including: catalyst dosage, suspension pH, visible light irradiation intensity, pollutant concentration and reaction time on efficiency of RO29 degradation was investigated. An enhancement in decolorization efficiency with decreasing suspension pH and increasing visible light irradiation intensity was observed. The optimum artificial neural network model yielded a determination coefficient of R2 = 0.9956 and showed that the relative effect of reaction time and catalyst dosage was higher than other investigated variables.