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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
Author(s) -
Khataee A.R.,
Vahid B.,
Behjati B.,
Safarpour M.
Publication year - 2013
Publication title -
environmental progress and sustainable energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.495
H-Index - 66
eISSN - 1944-7450
pISSN - 1944-7442
DOI - 10.1002/ep.11657
Subject(s) - cathode , carbon nanotube , electrolyte , volumetric flow rate , electrochemistry , electrode , carbon fibers , supporting electrolyte , materials science , degradation (telecommunications) , chemistry , analytical chemistry (journal) , chemical engineering , nuclear chemistry , chromatography , composite material , electrical engineering , physics , quantum mechanics , composite number , engineering
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 Fe 3+ 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 Fe 3+ 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 ( R 2 = 0.958). © 2012 American Institute of Chemical Engineers Environ Prog, 32: 557–563, 2013