Machine learning-assisted optimization of multi-metal hydroxide electrocatalysts for overall water splitting

Machine learning-assisted optimization of multi-metal hydroxide electrocatalysts for overall water splitting

Materials Horizons

10.1039/D3MH00788J

http://dx.doi.org/10.1039/d3mh00788j

Carina Yi Jing Lim, Riko I Made, Zi Hui Jonathan Khoo, Chee Koon Ng, Yang Bai, Jianbiao Wang, Gaoliang Yang, Albertus D. Handoko, Yee-Fun Lim

Electrical and Electronic Engineering, General Materials Science, Mechanics of Materials, Process Chemistry and Technology

21 August 2023

Lim, C. Y. J., I Made, R., Khoo, Z. H. J., Ng, C. K., Bai, Y., Wang, J., Yang, G., Handoko, A. D., & Lim, Y.-F. (2023). Machine learning-assisted optimization of multi-metal hydroxide electrocatalysts for overall water splitting. Materials Horizons. https://doi.org/10.1039/d3mh00788j

Development of electrocatalysts may be aided by machine learning integration into experimental workflows.

Publisher Copyright

This research / project is supported by the Agency for Science, Technology and Research (A*STAR) - Accelerated Catalysis Development Platform
Grant Reference no. : A19E9a0103

https://oar.a-star.edu.sg/communities-collections/articles/19261

2051-6347
2051-6355

Institute of Sustainability for Chemicals, Energy and Environment