화학공학소재연구정보센터
Chemical Engineering Research & Design, Vol.127, 113-125, 2017
Photocatalytic activity of g-C3N4: An empirical kinetic model, optimization by neuro-genetic approach and identification of intermediates
The polymeric graphitic carbon nitride (g-C3N4) was synthesized via direct heating of melamine precursor. The obtained solid was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), UV-vis diffuse reflection spectra (DRS) and Fourier transform infrared (FT-IR). The photocatalytic performance of the synthesized g-C3N4 was investigated by photodegradation of Reactive Black 5 as a model organic pollutant. The removal efficiency of dye over g-C3N4 was yielded 95% after 120 min. The effect of operational parameters including pH, catalyst dosage and dye initial concentration was investigated. An artificial neural network-genetic algorithm approach was utilized to find the optimal conditions for achieving maximum degradation efficiency. A nonlinear empirical kinetic model was also developed to predict the first order rate constant (k(app)). The photocatalytic degradation intermediates were identified using GC-MS and a probable degradation pathway was proposed. (C) 2017 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.