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Cited by 259

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Reaction Pathways for Oxygen Evolution Promoted by Cobalt Catalyst

Open access
Mattioli, Giuseppe, Giannozzi, Paolo, Amore Bonapasta, Aldo, Guidoni, Leonardo·2013·Journal of the American Chemical Society

Abstract

The in-depth understanding of the molecular mechanisms regulating the water oxidation catalysis is of key relevance for the rationalization and the design of efficient oxygen evolution catalysts based on earth-abundant transition metals. Performing ab initio DFT+U molecular dynamics calculations of cluster models in explicit water solution, we provide insight into the pathways for oxygen evolution of a cobalt-based catalyst (CoCat). The fast motion of protons at the CoCat/water interface and the occurrence of cubane-like Co-oxo units at the catalyst boundaries are the keys to unlock the fast formation of O-O bonds. Along the resulting pathways, we identified the formation of Co(IV)-oxyl species as the driving ingredient for the activation of the catalytic mechanism, followed by their geminal coupling with O atoms coordinated by the same Co. Concurrent nucleophilic attack of water molecules coming directly from the water solution is discouraged by high activation barriers. The achieved results suggest also interesting similarities between the CoCat and the Mn4Ca-oxo oxygen evolving complex of photosystem II.

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Crossref · 10.1021/ja401797v

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Metadata

Authors
Mattioli, G., Giannozzi, P., Amore Bonapasta, A., & Guidoni, L.
Venue
Journal of the American Chemical Society
Published
2013-10-03
Volume
135
Issue
41
Pages
15353-15363
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2169796085
Cited by
259
References
2
FWCI
8.42
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.