A Universal Machine Learning Framework for Electrocatalyst Innovation: A Case Study of Discovering Alloys for Hydrogen Evolution Reaction-Reference-Cited by-同舟云学术

A Universal Machine Learning Framework for Electrocatalyst Innovation: A Case Study of Discovering Alloys for Hydrogen Evolution Reaction

Published:2022-09-16 Issue:47 Volume:32 Page:2208418
ISSN:1616-301X
Container-title:Advanced Functional Materials
language:en
Short-container-title:Adv Funct Materials

Author:

Chen Letian¹,Tian Yun²,Hu Xu¹,Yao Sai¹,Lu Zhengyu¹,Chen Suya¹,Zhang Xu²,Zhou Zhen¹²^ORCID

Affiliation:

1. School of Materials Science and Engineering Institute of New Energy Material Chemistry Renewable Energy Conversion and Storage Center (ReCast) Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) Nankai University Tianjin 300350 China

2. School of Chemical Engineering Zhengzhou University Zhengzhou 450001 China

Funder

National Natural Science Foundation of China

Tianjin Research Innovation Project for Postgraduate Students

Publisher

Wiley

Subject

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

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adfm.202208418

Reference56 articles.

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