Abstract
Automatic mechanism generation is used to determine mechanisms for the CO2 hydrogenation on Ni(111) in a two-stage process while considering the correlated uncertainty in DFT-based energetic parameters systematically. In a coarse stage, all the possible chemistry is explored with gas-phase products down to the ppb level, while a refined stage discovers the core methanation submechanism. Five thousand unique mechanisms were generated, which contain minor perturbations in all parameters. Global uncertainty assessment, global sensitivity analysis, and degree of rate control analysis are performed to study the effect of this parametric uncertainty on the microkinetic model predictions. Comparison of the model predictions with experimental data on a Ni/SiO2 catalyst find a feasible set of microkinetic mechanisms within the correlated uncertainty space that are in quantitative agreement with the measured data, without relying on explicit parameter optimization. Global uncertainty and sensitivity analyses provide tools to determine the pathways and key factors that control the methanation activity within the parameter space. Together, these methods reveal that the degree of rate control approach can be misleading if parametric uncertainty is not considered. The procedure of considering uncertainties in the automated mechanism generation is not unique to CO2 methanation and can be easily extended to other challenging heterogeneously catalyzed reactions.
Original language | English |
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Pages (from-to) | 1656-1673 |
Number of pages | 18 |
Journal | JACS Au |
Volume | 1 |
Issue number | 10 |
DOIs | |
State | Published - Oct 25 2021 |
Externally published | Yes |
Funding
B.K. gratefully acknowledges financial support from the NaWuReT (ProcessNet, DECHEMA) for a virtual research collaboration with CFG in the fall of 2020. B.K. and T.T. acknowledge financial support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project no. 290019031. K.S., E.M., K.B., R.H.W., and C.F.G. gratefully acknowledge support by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under Award No. 0000232253, as part of the Computational Chemical Sciences Program. B.K. and C.F.G. thank Habib Najm and Judit Zádor for helpful discussions on sensitivity analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Keywords
- RMG
- carbon dioxide
- global uncertainty analysis
- methanation
- rate-based algorithm