Machine learning narrows search for green ammonia catalysts

MIT researchers have developed a computational method to identify promising catalyst materials for electrochemical ammonia synthesis, potentially replacing the energy-intensive Haber-Bosch process. The approach focuses on key physical properties that drive catalytic activity, avoiding slow trial-and-error testing of millions of alloy combinations. The findings, published in EES Catalysis, could accelerate the development of low-emission ammonia production.