Remediation/Treatment
Treatment of a dye solution using photoelectro-fenton process on the cathode containing carbon nanotubes under recirculation mode: Investigation of operational parameters and artificial neural network modeling
Article first published online: 12 JUN 2012
DOI: 10.1002/ep.11657
Copyright © 2012 American Institute of Chemical Engineers (AIChE)
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Environmental Progress & Sustainable Energy
Early View (Online Version of Record published before inclusion in an issue)
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How to Cite
Khataee, A.R., Vahid, B., Behjati, B. and Safarpour, M. (2012), Treatment of a dye solution using photoelectro-fenton process on the cathode containing carbon nanotubes under recirculation mode: Investigation of operational parameters and artificial neural network modeling. Environ. Prog. Sustainable Energy. doi: 10.1002/ep.11657
Publication History
- Article first published online: 12 JUN 2012
- Manuscript Accepted: 13 MAY 2012
- Manuscript Revised: 1 APR 2012
- Manuscript Received: 9 JAN 2012
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Keywords:
- electrochemical treatment;
- carbon nanotubes;
- azo dye;
- ANN modeling
Abstract
The electrochemical treatment of dye solution containing C.I. Direct Red 23 (DR23) has been studied under recirculation mode with an UV irradiation of 15 W. Decolorization experiments were performed in the presence of sulfate electrolyte media at pH 3.0 with carbon nanotube-polytetrafluoroethylene (CNT-PTFE) electrode as cathode. A comparison of electro-Fenton (EF) and photoelectro-Fenton (PEF) processes was carried out for decolorization of DR23 solution. Color removal efficiency was 66.22% and 94.29% for EF and PEF processes after 60 min treatment of 30 mg/L DR23, respectively. The effect of operational parameters on the PEF process such as applied current, initial pH, flow rate, initial Fe3+ concentration and initial dye concentration was investigated. Results indicated that the optimal conditions for decolorization process were applied current of 0.2 A, flow rate of 10 L/h, pH = 3, initial Fe3+ concentration of 0.05 mM and initial dye concentration of 10 mg/L. An artificial neural network (ANN) model was developed to predict the decolorization of DR23 solution, which provided reasonable predictive performance (R2 = 0.958). © 2012 American Institute of Chemical Engineers Environ Prog, 2012

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