Toward Excellence of Electrocatalyst Design by Emerging Descriptor‐Oriented Machine Learning-Reference-Cited by-同舟云学术

Toward Excellence of Electrocatalyst Design by Emerging Descriptor‐Oriented Machine Learning

Published:2022-01-15 Issue:17 Volume:32 Page:2110748
ISSN:1616-301X
Container-title:Advanced Functional Materials
language:en
Short-container-title:Adv Funct Materials

Author:

Liu Jianwen¹^ORCID,Luo Wenzhi¹,Wang Lei¹,Zhang Jiujun²,Fu Xian‐Zhu¹,Luo Jing‐Li¹

Affiliation:

1. Shenzhen Key Laboratory of Polymer Science and Technology Guangdong Research Center for Interfacial Engineering of Functional Materials College of Materials Science and Engineering Shenzhen University Shenzhen 518060 China

2. Institute for Sustainable Energy College of Sciences Shanghai University Shanghai 200444 China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrochemistry,Condensed Matter Physics,Biomaterials,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adfm.202110748

Reference195 articles.

1. Accelerated discovery of CO2 electrocatalysts using active machine learning

2. Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing

3. Combining theory and experiment in electrocatalysis: Insights into materials design

4. Machine learning for molecular and materials science

5. Extracting Knowledge from Data through Catalysis Informatics

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