Chemical Engineering Communications, Vol.204, No.7, 729-738, 2017
High-Performance Nanocatalyst for Adsorptive and Photo-Assisted Fenton-Like Degradation of Phenol: Modeling Using Artificial Neural Networks
High-performance activated carbon-zinc oxide (Ac-ZnO) nanocatalyst was fabricated via the microwave-assisted technique. Ac-ZnO was characterized and the results indicated that Ac-ZnO is stable, had a band gap of 3.26eV and a surface area of 603.5m(2)g(-1), and exhibited excellent adsorptive and degrading potentials. About 93% phenol was adsorbed within 550min of reaction by Ac-ZnO. Impressively, a complete degradation was achieved in 90min via a photo-Fenton/Ac-ZnO system under optimum conditions. An artificial neural network (ANN) model was developed and applied to study the relative significance of input variables affecting the degradation of phenol in a photo-Fenton process. The ANN results indicate that increases in both H2O2 and Ac-ZnO dosage enhanced the rate of phenol degradation. The highest rate constant at the optimum conditions was 0.093min(-1) and it was found to be consistent with the ANN-predicted rate constant (0.095min(-1)).
Keywords:Activated carbon;Artificial neural network;Fenton-like degradation;Phenol;ZnO nanoparticles