Energy Environ. Sci., 2023, Advance Article
DOI: 10.1039/D3EE01981K, Paper
DOI: 10.1039/D3EE01981K, Paper
Doudou Zhang, Haobo Li, Haijiao Lu, Zongyou Yin, Zelio Fusco, Asim Riaz, Karsten Reuter, Kylie Catchpole, Siva Karuturi
A machine-learning methodology was applied to unveil the structure–property relationships of the fabricated ternary Ni, Fe, and Co amorphous oxygen evolution catalyst, showcasing remarkable performance and stability via corrosion engineering.
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A machine-learning methodology was applied to unveil the structure–property relationships of the fabricated ternary Ni, Fe, and Co amorphous oxygen evolution catalyst, showcasing remarkable performance and stability via corrosion engineering.
To cite this article before page numbers are assigned, use the DOI form of citation above.
The content of this RSS Feed (c) The Royal Society of Chemistry