Optimization and Modeling of CuOx/OMWNT’s for Catalytic Reduction of Nitrogen Oxides by Response Surface Methodology
Publish Year: 1398
نوع سند: مقاله ژورنالی
زبان: English
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JR_IJOGST-8-1_004
تاریخ نمایه سازی: 22 تیر 1398
Abstract:
A series of copper oxide (CuOx) catalysts supported by oxidized multi-walled carbon nanotubes (OMWNT’s) were prepared by the wet impregnation method for the low temperature (200 °C) selective catalytic reduction of nitrogen oxides (NOx) using NH3 as a reductant agent in the presence of excess oxygen. These catalysts were characterized by FTIR, XRD, SEM-EDS, and H2-TPR methods. The response surface methodology was employed to model and optimize the effective parameters in the preparation of CuOx/OMWNT’s catalysts in NOx removal by NH3-SCR process. Three experimental parameters, including calcination temperature, calcination time, and CuOx loading were chosen as the independent variables. The central composite design was utilized to establish a quadratic model as a functional relationship between the conversion of NOx as a response factor and independent variables. The ANOVA results showed that the NOx conversion is significantly affected by calcination temperature and CuOx loading. At the optimal values of the studied parameters, the maximum conversion of NOx, 86.3 %, was obtained at a calcination temperature of 318 °C, a calcination time of 3.4 hr., and CuOx loading of 16.73 wt.%; the reaction conditions was as follows: T= 200 °C, P= 1 bar, NO = NH3 = 900 ppm, O2 = 5 vol.%, and GHSV = 30,000 hr.−1. The regression analysis with an R2value of 0.9908 revealed a satisfactory correlation between the experimental data and the values predicted for the conversion of NOx. The XRD and H2-TPR results of the best catalyst showed that the formation of CuO as the dominant phase of CuOx is the key factor in low temperature selective catalytic reduction (SCR) process.
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Authors
Mahnaz Pourkhalil
Assistance Professor, Nanotechnology Research Center, Research Institute of the Petroleum Industry, Tehran, Iran
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