Catalytic Conversion of Alkenes on Acidic Zeolites: Automated Generation of Reaction Mechanisms and Lumping Technique.
| Autor: | Koninckx E; Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States., Colin JG; Department of Chemical and Biological Engineering, University of Sheffield, Sheffield S1 3JD, United Kingdom., Broadbelt LJ; Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States., Vernuccio S; Department of Chemical and Biological Engineering, University of Sheffield, Sheffield S1 3JD, United Kingdom. |
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| Jazyk: | angličtina |
| Zdroj: | ACS engineering Au [ACS Eng Au] 2022 Jun 15; Vol. 2 (3), pp. 257-271. Date of Electronic Publication: 2022 Apr 01. |
| DOI: | 10.1021/acsengineeringau.2c00004 |
| Abstrakt: | Acid-catalyzed hydrocarbon transformations are essential for industrial processes, including oligomerization, cracking, alkylation, and aromatization. However, these chemistries are extremely complex, and computational (automatic) reaction network generation is required to capture these intricacies. The approach relies on the concept that underlying mechanisms for the transformations can be described by a limited number of reaction families applied to various species, with both gaseous and protonated intermediate species tracked. Detailed reaction networks can then be tailored to each industrially relevant process for better understanding or for application in kinetic modeling, which is demonstrated here. However, we show that these networks can grow very large (thousands of species) when they are bound by typical carbon number and rank criteria, and lumping strategies are required to decrease computational expense. For acid-catalyzed hydrocarbon transformations, we propose lumping isomers based on carbon number, branch number, and ion position to reach high carbon limits while maintaining the high resolution of species. Two case studies on propene oligomerization verified the lumping technique in matching a fully detailed model as well as experimental data. Competing Interests: The authors declare no competing financial interest. (© 2022 The Authors. Published by American Chemical Society.) |
| Databáze: | MEDLINE |
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