MIT Uses Machine Learning to Speed Up Green Ammonia Catalyst Discovery
MIT News AI · rss · 2026-08-21
MIT researchers developed a method using machine learning and density functional theory to predict the best catalysts for electrochemical ammonia production from millions of potential alloys. Traditional Haber-Bosch is energy-intensive, while electrochemical methods are greener but inefficient. The study aims to replace trial-and-error by identifying key physical properties, accelerating the discovery of highly active nitride catalysts to make green ammonia commercially viable.
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