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Cited by 299

The DOI matches its Crossref record; 408 of the 408 references it cites were found in a registry or an index.

Adsorption Energy in Oxygen Electrocatalysis

Zhang, Junming, Yang, Hong Bin, Zhou, Daojin, Liu, Bin·2022·Chemical Reviews

Abstract

Adsorption energy (AE) of reactive intermediate is currently the most important descriptor for electrochemical reactions (e.g., water electrolysis, hydrogen fuel cell, electrochemical nitrogen fixation, electrochemical carbon dioxide reduction, etc.), which can bridge the gap between catalyst's structure and activity. Tracing the history and evolution of AE can help to understand electrocatalysis and design optimal electrocatalysts. Focusing on oxygen electrocatalysis, this review aims to provide a comprehensive introduction on how AE is selected as the activity descriptor, the intrinsic and empirical relationships related to AE, how AE links the structure and electrocatalytic performance, the approaches to obtain AE, the strategies to improve catalytic activity by modulating AE, the extrinsic influences on AE from the environment, and the methods in circumventing linear scaling relations of AE. An outlook is provided at the end with emphasis on possible future investigation related to the obstacles existing between adsorption energy and electrocatalytic performance.

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Crossref · 10.1021/acs.chemrev.1c01003

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Metadata

Authors
Zhang, J., Yang, H. B., Zhou, D., & Liu, B.
Venue
Chemical Reviews
Published
2022-09-22
Volume
122
Issue
23
Pages
17028-17072
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W4296797703
Cited by
299
References
408
FWCI
2.86
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Adsorption Energy in Oxygen Electrocatalysis. https://app.cochat.ai/papers/10.1021/acs.chemrev.1c01003
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Zhang, J., Yang, H. B., Zhou, D., & Liu, B. (2022). Adsorption Energy in Oxygen Electrocatalysis. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.1c01003

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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).

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