Journal
ADVANCED FUNCTIONAL MATERIALS
Volume 32, Issue 38, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.202206163
Keywords
artificial intelligence; atomic-level catalyst designs; hydrogen evolution reactions; MoS; (2)
Categories
Funding
- National Funds for Distinguished Young Scientists [61825503]
- Natural Science Foundation of China [51902101, 61775101, 61804082]
- Youth Natural Science Foundation of Hunan Province [2019JJ50044]
- Natural Science Foundation of Jiangsu Province [BK20201381]
- Science Foundation of Nanjing University of Posts and Telecommunications [NY219144]
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Atom-economic catalysts offer a new way for computationally driven atomistic design of catalysts. This study focuses on MoS2 as a representative material and explores the relationship between different active-site configurations and catalytic activity. The findings provide insights for the design of high-performance MoS2-based catalysts in the future.
Atom-economic catalysts open a new era of computationally driven atomistic design of catalysts. Rationally manipulating the structures of the catalyst with atomic-level precision would definitely play a significant role in the future chemical industry. Of particular concern, there are growing research concentrating on MoS2 as a typical representative of transition metal dichalcogenides for its great potential of diverse atomic-level reactive sites for applications in catalysis for hydrogen evolution reaction. At present, the rational design of MoS2-based catalysts greatly depends on the comprehensive understanding of its structure-activity relationships of active sites that still lacks the systematic summary. In this regard, we dissected the internal relationships between diverse active-site configurations of MoS2 and the corresponding catalytic activity theoretically and experimentally to give impetus to the design of next-generation high-performance MoS2-based catalysts. The necessity of normalizing the existing activity evaluation methodology and developing more-precise metrics is discussed. Moreover, the advancement of artificial intelligence as an effective tool for the research on physicochemical properties of catalysts as well as its important role in theoretical pre-design has also been reviewed. Finally, we summarized the opportunities and challenges of the design of nanoscale catalysts with desired physicochemical properties by assembling atoms in a controllable way.
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