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Conflict of Interest: In relation to this article, we declare that there is no conflict of interest.

Publication history: Received January 13, 2010
Accepted June 17, 2010

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Statistical optimization of Rhodamine B removal by factorial design using reaction rate constant in electrochemical reaction

Youngwoong Song Dongseog Kim¹ Youngseek Park^2†

Department of Occupational Health, Catholic University of Daegu, Gyeongbuk 712-702, Korea ¹Department of Environmental Science, Catholic University of Daegu, Gyeongbuk 712-702, Korea ²Faculty of Liberal Education, Daegu University, Gyeongbuk 712-830, Korea

Korean Journal of Chemical Engineering, January 2011, 28(1), 156-163(8), 10.1007/s11814-010-0361-x

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Abstract

This study elucidates the reduction of Rhodamine B (RhB) color through electrochemical oxidation technique. Effects of current density, electrolyte type, electrolyte concentration, air flow rate and pH on the RhB color removal were investigated. The 2^(4) full factorial design was used to investigate the individual and combined effects of the current density, NaCl concentration, air flow rate, and pH. Also, this study tested the reaction constant rate (k) regression models as an alternative response surface model for the optimization of operating conditions. Increase of pH_x000D_ decreased the RhB color removal efficiency. At the same time, the increase of current density, NaCl concentration, air flow rate also increased the RhB color removal efficiency. From the 2^(4) factorial design, it was found that the individual main effects and four interaction effects (combined effects) of the independent variables were statistically significant (p<0.05). Also, the prediction results of the RhB concentration using the k regression models showed a nonlinear pattern which was similar to the actual experimental results. In the RhB color removal reactions, the 1st order k regression model showed a smaller prediction error than the 2nd order k regression model.

Keywords

Factorial Design Reaction Rate Constant k Regression Model Rhodamine B Electrochemical Treatment Ru-Sn-Sb Electrode

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