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Progress and Challenges Toward the Rational Design of Oxygen Electrocatalysts Based on a Descriptor Approach
Oxygen redox catalysis, including the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), is crucial in determining the electrochemical performance of energy conversion and storage devices such as fuel cells, metal–air batteries,and electrolyzers. The rational design of electrochemi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947511/ https://www.ncbi.nlm.nih.gov/pubmed/31921555 http://dx.doi.org/10.1002/advs.201901614 |
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author | Liu, Jieyu Liu, Hui Chen, Haijun Du, Xiwen Zhang, Bin Hong, Zhanglian Sun, Shuhui Wang, Weichao |
author_facet | Liu, Jieyu Liu, Hui Chen, Haijun Du, Xiwen Zhang, Bin Hong, Zhanglian Sun, Shuhui Wang, Weichao |
author_sort | Liu, Jieyu |
collection | PubMed |
description | Oxygen redox catalysis, including the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), is crucial in determining the electrochemical performance of energy conversion and storage devices such as fuel cells, metal–air batteries,and electrolyzers. The rational design of electrochemical catalysts replaces the traditional trial‐and‐error methods and thus promotes the R&D process. Identifying descriptors that link structure and activity as well as selectivity of catalysts is the key for rational design. In the past few decades, two types of descriptors including bulk‐ and surface‐based have been developed to probe the structure–property relationships. Correlating the current descriptors to one another will promote the understanding of the underlying physics and chemistry, triggering further development of more universal descriptors for the future design of electrocatalysts. Herein, the current benchmark activity descriptors for oxygen electrocatalysis as well as their applications are reviewed. Particular attention is paid to circumventing the scaling relationship of oxygen‐containing intermediates. For hybrid materials, multiple descriptors will show stronger predictive power by considering more factors such as interface reconstruction, confinement effect, multisite adsorption, etc. Machine learning and high‐throughput simulations can thus be crucial in assisting the discovery of new multiple descriptors and reaction mechanisms. |
format | Online Article Text |
id | pubmed-6947511 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69475112020-01-09 Progress and Challenges Toward the Rational Design of Oxygen Electrocatalysts Based on a Descriptor Approach Liu, Jieyu Liu, Hui Chen, Haijun Du, Xiwen Zhang, Bin Hong, Zhanglian Sun, Shuhui Wang, Weichao Adv Sci (Weinh) Reviews Oxygen redox catalysis, including the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), is crucial in determining the electrochemical performance of energy conversion and storage devices such as fuel cells, metal–air batteries,and electrolyzers. The rational design of electrochemical catalysts replaces the traditional trial‐and‐error methods and thus promotes the R&D process. Identifying descriptors that link structure and activity as well as selectivity of catalysts is the key for rational design. In the past few decades, two types of descriptors including bulk‐ and surface‐based have been developed to probe the structure–property relationships. Correlating the current descriptors to one another will promote the understanding of the underlying physics and chemistry, triggering further development of more universal descriptors for the future design of electrocatalysts. Herein, the current benchmark activity descriptors for oxygen electrocatalysis as well as their applications are reviewed. Particular attention is paid to circumventing the scaling relationship of oxygen‐containing intermediates. For hybrid materials, multiple descriptors will show stronger predictive power by considering more factors such as interface reconstruction, confinement effect, multisite adsorption, etc. Machine learning and high‐throughput simulations can thus be crucial in assisting the discovery of new multiple descriptors and reaction mechanisms. John Wiley and Sons Inc. 2019-11-27 /pmc/articles/PMC6947511/ /pubmed/31921555 http://dx.doi.org/10.1002/advs.201901614 Text en © 2019 The Authors. Published by WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Reviews Liu, Jieyu Liu, Hui Chen, Haijun Du, Xiwen Zhang, Bin Hong, Zhanglian Sun, Shuhui Wang, Weichao Progress and Challenges Toward the Rational Design of Oxygen Electrocatalysts Based on a Descriptor Approach |
title | Progress and Challenges Toward the Rational Design of Oxygen Electrocatalysts Based on a Descriptor Approach |
title_full | Progress and Challenges Toward the Rational Design of Oxygen Electrocatalysts Based on a Descriptor Approach |
title_fullStr | Progress and Challenges Toward the Rational Design of Oxygen Electrocatalysts Based on a Descriptor Approach |
title_full_unstemmed | Progress and Challenges Toward the Rational Design of Oxygen Electrocatalysts Based on a Descriptor Approach |
title_short | Progress and Challenges Toward the Rational Design of Oxygen Electrocatalysts Based on a Descriptor Approach |
title_sort | progress and challenges toward the rational design of oxygen electrocatalysts based on a descriptor approach |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947511/ https://www.ncbi.nlm.nih.gov/pubmed/31921555 http://dx.doi.org/10.1002/advs.201901614 |
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