Photoelectro-Fenton combined with photocatalytic process for degradation of an azo dye using supported TiO2 nanoparticles and carbon nanotube cathode: Neural network modeling

被引:142
作者
Zarei, M. [1 ]
Khataee, A. R. [1 ]
Ordikhani-Seyedlar, R. [1 ]
Fathinia, M. [1 ]
机构
[1] Univ Tabriz, Fac Chem, Dept Appl Chem, Tabriz, Iran
关键词
TiO2; nanoparticles; Carbon nanotube; Photocatalysis; TOC; Neural network; ADVANCED OXIDATION PROCESSES; INDIRECT ELECTROCHEMICAL TREATMENT; PEROXI-COAGULATION METHOD; ELECTRO-FENTON; AQUEOUS-MEDIUM; PHOTO-FENTON; HYDROGEN-PEROXIDE; ANODIC-OXIDATION; UVA LIGHT; WATER;
D O I
10.1016/j.electacta.2010.07.050
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
In this work, treatment of an azo dye solution containing C I Basic Red 46 (BR46) by photoelectro-Fenton (PEF) combined with photocatalytic process was studied Carbon nanotube-polytetrafluoroethylene (CNT-PTFE) electrode was used as cathode The investigated photocatalyst was TiO2 nanoparticles (Degussa P25) having 80% anatase and 20% nude, specific sur face area (BET) 50 m(2)/g, and particle size 21 nm immobilized on glass plates A comparison of electro-Fenton (EF), UV/TiO2, PEF and PEF/TiO2 processes for decolorization of BR46 solution was pet for med. Results showed that color removal follows the decreasing order PEF/TiO2> PEF> EF > UV/TiO2 The influence of the basic operational parameters such as initial pH of the solution, initial dye concentration, the size of anode. applied current. kind of ultraviolet (UV) light and initial Fe3+ concentration on the degradation efficiency of BR46 was studied The mineralization of the dye was investigated by total organic carbon (TOC) measurements that showed 98 8% mineralization of 20 mg/l dye at 6 h using PEF/TiO2 process An artificial neural network (ANN) model was developed to pi edict the decolorization of BR46 solution The findings indicated that artificial neural network provided reasonable predictive performance (R-2=0 986) (C) 2010 Elsevier Ltd All rights reserved
引用
收藏
页码:7259 / 7265
页数:7
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