The DOI matches its Crossref record; 174 of the 174 references it cites were found in a registry or an index.
Theoretical Heterogeneous Catalysis: Scaling Relationships and Computational Catalyst Design
Open accessAbstract
Scaling relationships are theoretical constructs that relate the binding energies of a wide variety of catalytic intermediates across a range of catalyst surfaces. Such relationships are ultimately derived from bond order conservation principles that were first introduced several decades ago. Through the growing power of computational surface science and catalysis, these concepts and their applications have recently begun to have a major impact in studies of catalytic reactivity and heterogeneous catalyst design. In this review, the detailed theory behind scaling relationships is discussed, and the existence of these relationships for catalytic materials ranging from pure metal to oxide surfaces, for numerous classes of molecules, and for a variety of catalytic surface structures is described. The use of the relationships to understand and elucidate reactivity trends across wide classes of catalytic surfaces and, in some cases, to predict optimal catalysts for certain chemical reactions, is explored. Finally, the observation that, in spite of the tremendous power of scaling relationships, their very existence places limits on the maximum rates that may be obtained for the catalyst classes in question is discussed, and promising strategies are explored to overcome these limitations to usher in a new era of theory-driven catalyst design.
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Cites
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Advances and challenges in understanding the electrocatalytic conversion of carbon dioxide to fuels
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Machine Learning for Catalysis Informatics: Recent Applications and Prospects
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Metadata
- Authors
- Greeley, J.
- Venue
- Annual Review of Chemical and Biomolecular Engineering
- Publisher
- Annual Reviews
- Published
- 2016-06-07
- Volume
- 7
- Issue
- 1
- Pages
- 605-635
- ISSN
- 1947-5438 (ISSN-L)
- 1947-5446
- OpenAlex
- W2341535801
- Cited by
- 409
- References
- 174
- FWCI
- 0.99
- Type
- journal article
- Language
- en
- Open access
- hybrid
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