Towards rational catalyst design: boosting the rapid prediction of transition-metal activity by improved scaling relations.

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ID: 36335
2019
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Ranked #80 of 184 articles by views in Physical chemistry chemical physics : PCCP

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Abstract
Understanding the scaling relations of adsorption energies and activation energies greatly facilitates the computational catalyst design. To reduce the computational cost and guarantee efficiency, improved scaling relations were advocated in this study to rapidly acquire the energetics for transition metal surface reactions and further to rapidly and effectively map the activity of transition-metal catalysts. The overall catalytic activity for the surface reactions between C-, H- and O-containing species could be related to their adsorption energies using C, H and O binding energies as descriptors via improved scaling relations. The UBI-QEP (unity bond index-quadratic exponential potential) method, one of the scaling relations used to estimate the adsorption energies from descriptors, was significantly improved by taking into account the changes in the A-B bond indexes during adsorption and the molecular structure of adsorbed species using density functional theory (DFT) data as a benchmark. The improved UBI-QEP approach could satisfactorily predict the DFT (BEEF-vdW) and experimental adsorption energies. DFT calculations with the BEEF-vdW functional were also employed for establishing the BEP (Brønsted-Evans-Polanyi) relationships as scaling relations to correlate the reaction heats with activation energies for C-H, C-O, C-C, and O-H bond cleavages and recombination. The capability of the improved UBI-QEP+BEP approach was tested as a generic framework to map the activity trend for steam methane reforming (a probe reaction) through microkinetic modeling. The results demonstrated that our approach reduces the computational cost by six orders of magnitude while maintaining a reasonable degree of accuracy as compared to the DFT (BEEF-vdW) and experimental approaches.
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wang2019towardsphysical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Wang, Yalan;Xiao, Ling;Qi, Yanying;Mahmoodinia, Mehdi;Feng, Xiang;Yang, Jia;Zhu, Yi-An;Chen, De;
Journal Physical chemistry chemical physics : PCCP
Year 2019
DOI
10.1039/c9cp04286e
URL
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