Accelerating materials discovery for electrocatalytic water oxidation <i>via</i> center-environment deep learning in spinel oxides-Reference-Cited by-同舟云学术

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Accelerating materials discovery for electrocatalytic water oxidation via center-environment deep learning in spinel oxides

Published:2024 Issue:30 Volume:12 Page:19362-19377
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Li Yihang¹^ORCID,Zhang Xinying¹,Li Tao¹,Chen Yingying¹^ORCID,Liu Yi¹^ORCID,Feng Lingyan¹²³^ORCID

Affiliation:

1. Materials Genome Institute, Shanghai University, Shanghai 200444, China

2. Shanghai Engineering Research Center of Organ Repair, School of Medicine, Shanghai University, Shanghai 200444, China

3. Joint International Research Laboratory of Biomaterials and Biotechnology in Organ Repair, Ministry of Education, School of Medicine, Shanghai University, Shanghai, 200444, China

Abstract

Using DFT and machine learning, we evaluated 5329 spinel oxides and identified 14 promising OER electrocatalysts. Experimentally, MoAg2O4 showed superior performance, achieving 10 mA cm−2 at 284 mV overpotential, surpassing commercial RuO2.

Funder

National Natural Science Foundation of China

Shanghai University

Shanghai Rising-Star Program

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/TA/D4TA02771J

Reference67 articles.

1. The frontiers of energy

2. The Future of Energy Supply: Challenges and Opportunities

3. The irreversible momentum of clean energy

4. Current status, research trends, and challenges in water electrolysis science and technology

5. Recent advances of ruthenium-based electrocatalysts for hydrogen energy

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