Automated Generation of Microkinetics for Heterogeneously Catalyzed Reactions Considering Correlated Uncertainties

08 May 2023, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


The study presents an ab-initio based framework for the automated construction of microkinetic mechanisms considering correlated uncertainties in all energetic parameters and estimation routines. Two thousand unique microkinetic models were generated within the uncertainty space of the BEEF-vdW functional for the conversion of exhaust gas emissions from stoichiometric gasoline combustion engines over Pt(111) and compared to experiments through multiscale modeling. The ensemble of simulations stresses the importance of considering uncertainties. Within this set of first-principles-based models, it is possible to identify a microkinetic mechanism that agrees with experimental data. This mechanism can be traced back to a single exchange-correlation functional, and it suggests that Pt(111) could be the active site for the oxidation of light hydrocarbons. The study provides a universal framework for the automated construction of reaction mechanisms with correlated uncertainty quantification, enabling a DFT-constrained microkinetic model optimization for other heterogeneously catalyzed systems.


Automated Mechanism Generation
Uncertainty Quantification
Reaction Mechanism

Supplementary materials

supporting information
Details on the experimental and computational methods, raw DFT data, additional results and discussion


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