Kinetic modeling of dynamically operated heterogeneously catalyzed reactions: Microkinetic model reduction and semi-mechanistic approach on the example of the CO2 methanation

被引:4
|
作者
Langer, Moritz [1 ]
Kellermann, David [1 ]
Freund, Hannsjoerg [1 ]
机构
[1] TU Dortmund Univ, Inst React Engn & Catalysis, Emil Figge Str 66, D-44227 Dortmund, Germany
关键词
Kinetic modeling; Catalyst surface; Dynamic operation; Model reduction; Green hydrogen; CO2; methanation; SURFACE-REACTION KINETICS; POWER-TO-GAS; CARBON-DIOXIDE; REACTORS; HYDROGENATION; STEAM;
D O I
10.1016/j.cej.2023.143217
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As the production of green hydrogen from fluctuating resources , the use of Power-to-X technologies become more and more important in the energy sector and the chemical process industries, the interest in dynamically operated reactors is increasing. In order to apply model-based optimization methods for process intensification the dynamic reactor behavior needs to be predicted sufficiently accurate by the underlying model equations, in which the reaction kinetics play a key role. Microkinetic elementary step models are able to describe the dynamic behavior on the catalyst surface. However, these models are laborious to derive, parameterize and require comparably high computational effort to solve. For these reasons, simpler semi-mechanistic kinetic models based on a rate determining step at steady state conditions are much more frequently applied in numerical studies. However, the underlying assumptions of these models are questionable for dynamic operation since sorption processes and possible changes in the reaction mechanisms are not considered. We present a semi-mechanistic kinetic model approach based on so called rate-affecting steps and the dynamic change in surface coverages, which is able to describe the dynamic behavior of the catalyst surface. The applicability of our approach is demonstrated for model reduction of an elementary step mechanism developed for the COx methanation and for kinetic model development with synthetic experimental data. Both methods result in a kinetic expression that can accurately reproduce the dynamic kinetic behavior predicted by the elementary step model, with a significant reduction in computational effort for our new semi-mechanistic model, making this new class of model approach attractive for model-based optimization applications.
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页数:16
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