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Catalytic properties of SmMnO3/cordierite monolithic catalysts: acid treatment and calcination process optimization using response surface methodology

This work focuses on the optimization of the acid treatment and calcination process factors affecting the catalytic performance of the SmMnO 3 /cordierite monolithic catalyst for o -xylene oxidation, using response surface methodology (RSM) analysis. A central composite rotatable design (CCRD) was u...

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Bibliographic Details
Published in:Journal of chemical sciences (Bangalore, India) India), 2022-06, Vol.134 (2), Article 46
Main Authors: BAO, LEI, WU, DONGFANG
Format: Article
Language:English
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Summary:This work focuses on the optimization of the acid treatment and calcination process factors affecting the catalytic performance of the SmMnO 3 /cordierite monolithic catalyst for o -xylene oxidation, using response surface methodology (RSM) analysis. A central composite rotatable design (CCRD) was used to statistically visualize the complex interactions of acid treatment time, acid concentration, calcination temperature, and calcination time for T 50 and T 90 values. And the validity of the models developed was verified by experiments. Statistics showed the most significant process factor which affects catalytic combustion activity is acid treatment time. It is also shown that the catalytic activity increases with increasing acid treatment time or acid concentration and that a moderate calcination temperature or time is required to increase the catalytic activity. Furthermore, it was found through SEM analysis that the acid treatment process significantly impacts the morphology of the SmMnO 3 /cordierite monolithic catalysts. Thus, RSM is an effective technique for estimating the catalytic activity of monolithic catalysts. Graphical abstract In this work, the effects of acid treatment and calcination process on the catalytic performance of SmMnO 3 /cordierite monolithic catalyst for o -xylene oxidation were based on response surface methodology (RSM) through presenting a mathematical modeling and factorial analysis.
ISSN:0974-3626
0973-7103
DOI:10.1007/s12039-022-02042-4