Single-atom alloy catalysts designed by first-principles calculations and artificial intelligence

Single-atom-alloy catalysts (SAACs) have recently become a frontier in catalysis research. Simultaneous optimization of reactants’ facile dissociation and a balanced strength of intermediates’ binding make them highly efficient catalysts for several industrially important reactions. However, discove...

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Bibliographic Details
Published in:Nature communications 2021-03, Vol.12 (1), p.1833-1833, Article 1833
Main Authors: Han, Zhong-Kang, Sarker, Debalaya, Ouyang, Runhai, Mazheika, Aliaksei, Gao, Yi, Levchenko, Sergey V.
Format: Article
Language:English
Subjects:
639/301/1034
639/301/299
639/638/563/606
Alloys
Artificial intelligence
Catalysis
Catalysts
Data analysis
Data mining
First principles
Humanities and Social Sciences
Intermediates
Mathematical analysis
multidisciplinary
Optimization
Qualitative analysis
Regression analysis
Regression models
Science
Science (multidisciplinary)
Single atom catalysts
Stability analysis
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Summary:Single-atom-alloy catalysts (SAACs) have recently become a frontier in catalysis research. Simultaneous optimization of reactants’ facile dissociation and a balanced strength of intermediates’ binding make them highly efficient catalysts for several industrially important reactions. However, discovery of new SAACs is hindered by lack of fast yet reliable prediction of catalytic properties of the large number of candidates. We address this problem by applying a compressed-sensing data-analytics approach parameterized with density-functional inputs. Besides consistently predicting efficiency of the experimentally studied SAACs, we identify more than 200 yet unreported promising candidates. Some of these candidates are more stable and efficient than the reported ones. We have also introduced a novel approach to a qualitative analysis of complex symbolic regression models based on the data-mining method subgroup discovery. Our study demonstrates the importance of data analytics for avoiding bias in catalysis design, and provides a recipe for finding best SAACs for various applications. Single-atom metal alloys attract considerable interest as alternative metal hydrogenation catalysts. Here the authors combine first-principles calculations with compressed-sensing data-analytics approaches to develop stability and activity’s descriptors for screening single atom alloy catalysts.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-021-22048-9