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High-Performance Nanocatalyst for Adsorptive and Photo-Assisted Fenton-Like Degradation of Phenol: Modeling Using Artificial Neural Networks.

Authors :
Gazi, Mustafa
Oladipo, Akeem Adeyemi
Ojoro, Zainab Eniola
Gulcan, Hayrettin Ozan
Source :
Chemical Engineering Communications. 2017, Vol. 204 Issue 7, p729-738. 10p.
Publication Year :
2017

Abstract

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 3.26 eV and a surface area of 603.5 m2g−1, and exhibited excellent adsorptive and degrading potentials. About 93% phenol was adsorbed within 550 min of reaction by Ac–ZnO. Impressively, a complete degradation was achieved in 90 min 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 0.093 min−1 and it was found to be consistent with the ANN-predicted rate constant (0.095 min−1). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00986445
Volume :
204
Issue :
7
Database :
Academic Search Index
Journal :
Chemical Engineering Communications
Publication Type :
Academic Journal
Accession number :
123763225
Full Text :
https://doi.org/10.1080/00986445.2017.1311253