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Machine learning assisted catalyst discovery advances green hydrogen production

In the News, Research
Overview of screening process for catalyst discovery


TRINA scientists achieved a breakthrough in catalyst search using a machine learning assisted method and published their work in the Journal of Energy Chemistry (impact factor: 13.6).

Green hydrogen production via water electrolysis has emerged as an appealing solution to the growing energy crisis and environmental issues, and has been pursued as one of the main strategies towards Toyota’s carbon neutrality mission. Since 2022, Toyota’s Material Research Department (MRD) materials informatics team has worked on the catalyst design to enhance the proton exchange membrane water electrolyzer for green hydrogen production. The team has developed a machine learning-aided high-throughput method to search for a novel catalyst. Using the in-house developed method, the team efficiently screened nearly 7,000 compounds, unveiling 61 promising candidates for future testing.

Transfer learning aided high-throughput computational design of oxygen evolution reaction catalysts in acid conditions