Literature DB >> 23943082

Photocatalytic discoloration of Methyl Orange by anatase/schorl composite: optimization using response surface method.

Huan-Yan Xu1, Wei-Chao Liu, Jian Shi, Hang Zhao, Shu-Yan Qi.   

Abstract

The anatase/schorl composites were prepared and employed for the photocatalytic discoloration of an azo dye, Methyl Orange (MO). X-ray diffraction results indicated that TiO2 existed in the form of anatase phase and no diffraction peaks of schorl could be observed for all the composite samples. Scanning electron micrographs showed that the particles of anatase were well deposited and dispersed on the surface of schorl. Photocatalytic experiments revealed that the anatase/schorl composites exhibited higher photocatalytic activity for MO discoloration than pure TiO2 and more than 90% discoloration ratio could be obtained within 60 min UV irradiation when the sample containing 3 wt.% of schorl as TiO2 support was used. Then, the central composite design (CCD) under the response surface methodology (RSM) was employed for the experiment design and process optimization. The significance of a second-order polynomial model for predicting the optimal values of MO discoloration was evaluated by the analysis of variance (ANOVA) and 3D response surface plots for the interactions between two variables were constructed. Based on the model prediction, the optimum conditions for the photocatalytic discoloration of MO by TiO2/schorl composite were determined to be 15 × 10(-3) mM MO initial concentration, 2.7 g/l photocatalyst dosage, solution pH 6.6 and 43 min reaction time, with a maximum MO discoloration ratio of 98.6%. Finally, a discoloration ratio of 94.3% was achieved for the real sample under the optimum conditions, which was very close to the predicted value, implying that RSM is a powerful and satisfactory strategy for the process optimization.

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Year:  2013        PMID: 23943082     DOI: 10.1007/s11356-013-2059-1

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


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