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Title
Photocatalytic activity of g-C3N4: An empirical kinetic model, optimization by neuro-genetic approach and identification of intermediates
Type of Research Article
Keywords
Graphitic carbon nitride Photocatalyst Genetic algorithm Empirical kinetic model
Abstract
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 (kapp). The photocatalytic degradation intermediates were identified using GC-MS and a probable degradation pathway was proposed.
Researchers Mir Saeed Seyed Dorraji (First Researcher)، Ali Reza Amani-Ghadim (Second Researcher)، Mohammad Hosein Rasoulifard (Third Researcher)، Hoda Daneshvar (Fourth Researcher)، إ Sistani Zadeh Aghdam (Fifth Researcher)، Ali Reza Tarighati (Not In First Six Researchers)، S.F. Hosseini (Not In First Six Researchers)