Accelerating the Discovery of Metastable IrO<sub>2</sub> for the Oxygen Evolution Reaction by the Self-Learning-Input Graph Neural Network-Reference-Cited by-同舟云学术

Accelerating the Discovery of Metastable IrO₂ for the Oxygen Evolution Reaction by the Self-Learning-Input Graph Neural Network

Published:2023-04-11 Issue:4 Volume:3 Page:1131-1140
ISSN:2691-3704
Container-title:JACS Au
language:en
Short-container-title:JACS Au

Author:

Feng Jie¹,Dong Zhihao¹,Ji Yujin¹^ORCID,Li Youyong¹²^ORCID

Affiliation:

1. Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, China

2. Macao Institute of Materials Science and Engineering, Macau University of Science and Technology, Taipa, Macau SAR 999078, China

Funder

Collaborative Innovation Center of Suzhou Nano Science and Technology

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

Fundo para o Desenvolvimento das Ci?ncias e da Tecnologia

National Natural Science Foundation of China

Priority Academic Program Development of Jiangsu Higher Education Institutions

Higher Education Discipline Innovation Project

Joint International Research Laboratory of Carbon-Based Functional Materials and Devices

Natural Science Foundation of Jiangsu Province

Publisher

American Chemical Society (ACS)

Subject

General Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/jacsau.2c00709

Reference69 articles.

1. Metallic nanostructures with low dimensionality for electrochemical water splitting

2. Activating lattice oxygen redox reactions in metal oxides to catalyse oxygen evolution

3. Electrolysis of water on oxide surfaces

4. Synthesis and Activities of Rutile IrO2 and RuO2 Nanoparticles for Oxygen Evolution in Acid and Alkaline Solutions

5. Considerations for the scaling-up of water splitting catalysts

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