Data-driven optimisation of more sustainable high-to-medium entropy Perovskites for oxygen evolution catalysts

Materials Horizons 2026 Open access

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Authors: Anis Arisa Roslan, Jack J. Quayle, Yuankai Zhao, Thomas E. Ashton, Jiacheng Wang, Stuart A. Bateman, Tu C. Le, Jawwad Arshad Darr
DOI: 10.1039/d6mh01015f
Cited by: 0
References: 174

Abstract

A high-throughput machine learning-guided synthesis and screening process for low-ruthenium Perovskite catalysts with champion samples achieving a 269 mV overpotential and over 100 h of durability, surpassing RuO 2 and IrO 2 benchmarks.

Fields of Study & Subjects

High Entropy Alloys Studies Electrocatalysts for Energy Conversion Advancements in Solid Oxide Fuel Cells

Publication details

Journal / source
Materials Horizons
Publication date
1 January 2026
Language
EN