Analysis of the oxygen evolution activity of layered double hydroxides (LDHs) using machine learning guidance-Reference-Cited by-同舟云学术

Analysis of the oxygen evolution activity of layered double hydroxides (LDHs) using machine learning guidance

Published:2023 Issue:11 Volume:25 Page:7917-7926
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Wei Chenyang¹,Shi Dingyi²,Zhou Fengyi¹,Yang Zhaohui¹,Zhang Zhenchuan¹,Xue Zhimin³^ORCID,Mu Tiancheng¹^ORCID

Affiliation:

1. Department of Chemistry, Renmin University of China, Beijing, 100872, China

2. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China

3. Beijing Key Laboratory of Lignocellulosic Chemistry, College of Materials Science and Technology, Beijing Forestry University, Beijing 100083, China

Abstract

Machine learning (ML) can help to design layered double hydroxides (LDHs) with excellent properties as catalysts for the oxygen evolution reaction (OER).

Funder

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2023/CP/D2CP06052C

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