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Kinetic Modeling: History
Please note this is an old version of this entry, which may differ significantly from the current revision.
Contributor: Jack Zhong

Kinetic modeling is the construction of a mathematical description of a reacting system in which every elementary step carries its own rate constant, so that the macroscopic rates and selectivities follow from the mechanism rather than being fitted directly. In heterogeneous catalysis this means writing the adsorption, surface reaction and desorption steps explicitly, then solving the resulting balance equations; the challenge is less the formalism than the parameter values, since activation barriers from electronic structure calculations carry errors that propagate through the model [1]. Closing the gap between predicted and measured rates and selectivities has become the benchmark by which such models are judged [2]. A concrete case shows what is involved: the oxidation of cis-cyclooctene over a grafted manganese complex has been described with a full microkinetic scheme [3]. Quantifying how parameter uncertainty propagates to the predicted rate is therefore part of the practice [4]. Automatic generation of the mechanism and of the corresponding equations reduces the manual effort that has limited the scope of these models [5].

  • microkinetic model
  • elementary step
  • rate constant
  • degree of rate control
  • parameter uncertainty
  • reaction network
  • selectivity prediction

 

 

References

  1. Majumdar, P.; Microkinetic Modeling in Heterogeneous Catalysis: Challenges and Path Forward. Journal of the Indian Institute of Science 2025, 105, 499-511, 10.1007/s41745-025-00482-8.
  2. Xie, W.; Xu, J.; Chen, J.; Wang, H.; Hu, P.; Achieving Theory–Experiment Parity for Activity and Selectivity in Heterogeneous Catalysis Using Microkinetic Modeling. Accounts of Chemical Research 2022, 55, 1237-1248, 10.1021/acs.accounts.2c00058.
  3. Bjorkman, K.R.; Schoenfeldt, N.J.; Notestein, J.M.; Broadbelt, L.J.; Microkinetic modeling of cis-cyclooctene oxidation on heterogeneous Mn–tmtacn complexes. Journal of Catalysis 2012, 291, 17-25, 10.1016/j.jcat.2012.03.026.
  4. Lu, Y.; Wang, B.; Chen, S.; Yang, B.; Quantifying the error propagation in microkinetic modeling of catalytic reactions with model-predicted binding energies. Molecular Catalysis 2022, 530, 112575, 10.1016/j.mcat.2022.112575.
  5. Ureel, Y.; Tomme, L.; Sabbe, M.K.; Van Geem, K.M.; Genesys-Cat: automatic microkinetic model generation for heterogeneous catalysis with improved Bayesian optimization. Catalysis Science & Technology 2025, 15, 750-764, 10.1039/d4cy01344a.
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