(8e) Uncertainty Quantification of Catalyst Structure Effects on Kinetics
AIChE Annual Meeting
2021
2021 Annual Meeting
Topical Conference: Applications of Data Science to Molecules and Materials
Applications of Data Science in Catalysis and Reaction Engineering I
Sunday, November 7, 2021 - 4:42pm to 5:00pm
Complete methane oxidation on noble metals is chosen as a case study due to many available published literature data. The structure sensitivity of this reaction has been debated experimentally for decades [2] due to the difficulty in identifying catalyst surface structures in situ. Structure-dependent kinetic modeling provides the possibility to explore it theoretically. Recently published computational work either chooses several common facets [3] or develops a structure-dependent model for archetypical simple reactions, such as CO oxidation [4]. There is a need to create suitable microkinetic models for describing structure sensitivity and explore structure effects.
In this work, we develop a novel methodology to build a structure-descriptor-based kinetic model for complete methane oxidation based on first-principles calculations. Structure-reactivity scaling relationships, reminiscent of the generalized coordination number (GCN) [5], are developed using machine learning techniques. By incorporating these correlations into kinetic models leveraging our in-house developed software, we predict the experimental observables, such as turnover frequencies (TOF) and apparent activation energies, at a dramatically reduced computational cost compared to first-principles calculations. Additionally, uncertainty quantification is applied for exploring the effects of errors in structure-reactivity scaling relations on variable catalyst facets. This methodology enables the rapid prediction of kinetics and quantifies the uncertainties due to the catalyst structure.
References
1. Cheula, R., Soon, A., and Maestri, M. Catal. Sci. Technol. 8, 3493 (2018).
2. Beck, Irene E. et al. J. Catal. 268, 60 (2009).
3. Wang, Y. et al. J. Phys. Chem. C 124, 2501 (2020).
4. Jørgensen, M. and Grönbeck, H. ACS Catal. 7, 5054 (2017).
5. Calle-Vallejo, F., Sautet, P. and Loffreda, D., Angew. Chemie - Int. Ed. 53, 8316 (2014).