Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst

Electrochemical CO2 reduction reaction (CO2RR) is an important process which is a potential way to recycle excessive CO2 in the atmosphere. Although the electrocatalyst is the key toward efficient CO2RR, the progress of discovering effective catalysts is lagging with current methods. Because of the...

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Main Authors:	Hu, Erhai, Liu, Chuntai, Zhang, Wei, Yan, Qingyu
Other Authors:	School of Materials Science and Engineering
Format:	Article
Language:	English
Published:	2023
Subjects:	Engineering::Materials Carbon Dioxide Machine Learning
Online Access:	https://hdl.handle.net/10356/168939
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-168939
record_format	dspace
spelling	sg-ntu-dr.10356-1689392023-06-23T03:21:49Z Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst Hu, Erhai Liu, Chuntai Zhang, Wei Yan, Qingyu School of Materials Science and Engineering Institute of Materials Research and Engineering, A*STAR Engineering::Materials Carbon Dioxide Machine Learning Electrochemical CO2 reduction reaction (CO2RR) is an important process which is a potential way to recycle excessive CO2 in the atmosphere. Although the electrocatalyst is the key toward efficient CO2RR, the progress of discovering effective catalysts is lagging with current methods. Because of the cost and time efficiency of the modern machine learning (ML) algorithm, an increasing number of researchers have applied ML to accelerate the screening of suitable catalysts and to deepen our understanding in the mechanism. Hence, we reviewed recent applications of ML in the research of CO2RR by the types of electrocatalyst. An introduction on the general methodology and a discussion on the pros and cons for such applications are included. Ministry of Education (MOE) Q.Y. acknowledges the funding support from Singapore MOE AcRF Tier 1 under Grant No. 2020-T1-001-031. 2023-06-23T03:19:44Z 2023-06-23T03:19:44Z 2023 Journal Article Hu, E., Liu, C., Zhang, W. & Yan, Q. (2023). Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst. Journal of Physical Chemistry C, 127(2), 882-893. https://dx.doi.org/10.1021/acs.jpcc.2c08343 1932-7447 https://hdl.handle.net/10356/168939 10.1021/acs.jpcc.2c08343 2-s2.0-85146164646 2 127 882 893 en 2020-T1-001-031 Journal of Physical Chemistry C © 2023 American Chemical Society. All rights reserved.
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Materials Carbon Dioxide Machine Learning
spellingShingle	Engineering::Materials Carbon Dioxide Machine Learning Hu, Erhai Liu, Chuntai Zhang, Wei Yan, Qingyu Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst
description	Electrochemical CO2 reduction reaction (CO2RR) is an important process which is a potential way to recycle excessive CO2 in the atmosphere. Although the electrocatalyst is the key toward efficient CO2RR, the progress of discovering effective catalysts is lagging with current methods. Because of the cost and time efficiency of the modern machine learning (ML) algorithm, an increasing number of researchers have applied ML to accelerate the screening of suitable catalysts and to deepen our understanding in the mechanism. Hence, we reviewed recent applications of ML in the research of CO2RR by the types of electrocatalyst. An introduction on the general methodology and a discussion on the pros and cons for such applications are included.
author2	School of Materials Science and Engineering
author_facet	School of Materials Science and Engineering Hu, Erhai Liu, Chuntai Zhang, Wei Yan, Qingyu
format	Article
author	Hu, Erhai Liu, Chuntai Zhang, Wei Yan, Qingyu
author_sort	Hu, Erhai
title	Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst
title_short	Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst
title_full	Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst
title_fullStr	Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst
title_full_unstemmed	Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst
title_sort	machine learning assisted understanding and discovery of co₂ reduction reaction electrocatalyst
publishDate	2023
url	https://hdl.handle.net/10356/168939
_version_	1772825265636900864

Machine learning assisted understanding and discovery of CO₂ reduction reaction electrocatalyst

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