Researchers from Tohoku University have used machine learning to expedite the discovery of high-performance metal oxide catalysts for the oxygen reduction reaction (ORR), which is crucial for renewable energy technologies. They analyzed 7,798 metal oxide catalysts and identified optimal compositions, such as Mn–Ca–La, Mn–Ca–Y, and Mn–Mg–Ca, for hydrogen fuel cells and hydrogen peroxide production. This method significantly reduces the time and resources needed for catalyst development, enhancing the efficiency and cost-effectiveness of renewable energy systems.
For more details, read the full article here: