详细信息
Determining apparent kinetics for catalyst pellets using particle-resolved computational fluid dynamics ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Determining apparent kinetics for catalyst pellets using particle-resolved computational fluid dynamics
作者:Yu, Daiyi[1];Zhang, Zhihua[1];Zheng, Yang[1];Song, Nan[1];Ye, Guanghua[1];Zhou, Xinggui[1]
机构:[1]East China Univ Sci & Technol, Sch Chem Engn, State Key Lab Chem Engn & Low Carbon Technol, Shanghai, Peoples R China
年份:2026
外文期刊名:AICHE JOURNAL
收录:;EI(收录号:20261020197980);WOS:【SCI-EXPANDED(收录号:WOS:001702379100001)】;
基金:This study was financially supported by the National Key Research and Development Program of China from the Ministry of Science and Technology of the People's Republic of China (2021YFA1501403), the Natural Science Foundation of China (U25A20600, 22038003, 22208093, and 22178100), the Innovation Program of the Shanghai Municipal Education Commission, the Program of Shanghai Academic/Technology Research Leader (21XD1421000).
语种:英文
外文关键词:apparent kinetics; catalyst pellet; non-ideal flow; PRCFD; propylene epoxidation
摘要:Conventional methods for determining apparent kinetics for fixed-bed reactor design require experiments under ideal flow conditions and with negligible external diffusion limitation, which are costly and inconvenient. This study proposes a new method for determining the apparent kinetics based on particle-resolved computational fluid dynamics (PRCFD) that can resolve the influence of inter-particle transfer. Using PRCFD allows kinetic measurements in fixed-bed reactors with minimal catalyst (down to a single pellet) loading and small gas velocity. Au/TS-1 catalyst pellets for propylene epoxidation are used to evaluate this method. The results show that this method can yield reliable apparent kinetics. PRCFD-based quantification confirms that non-ideal flow and transport limitations are significant, necessitating PRCFD for accurate determination of apparent kinetics. A comparison reveals that the material cost of this method can be three orders of magnitude lower than that of a conventional method at the expense of an increased but acceptable computational cost.
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