Amorphous Catalysis: Machine Learning Driven High-Throughput Screening of Superior Active Site for Hydrogen Evolution Reaction-Reference-Cited by-同舟云学术

Amorphous Catalysis: Machine Learning Driven High-Throughput Screening of Superior Active Site for Hydrogen Evolution Reaction

Published:2020-04-22 Issue:19 Volume:124 Page:10483-10494
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Zhang Jiawei¹,Hu Peijun¹²^ORCID,Wang Haifeng¹^ORCID

Affiliation:

1. Key Laboratory for Advanced Materials, Research Institute of Industrial Catalysis and Centre for Computational Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, P. R. China

2. School of Chemistry and Chemical Engineering, The Queen’s University of Belfast, Belfast, BT9 5AG, U.K.

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.0c00406

Reference82 articles.

1. Widely available active sites on Ni2P for electrochemical hydrogen evolution – insights from first principles calculations