Smarter search for fuel-cell catalysts uses machine learning
A computational method combining generative AI with atomistic simulations can identify promising platinum alloy catalyst structures for hydrogen fuel cells, report researchers from Science Tokyo. Their approach addresses a longstanding challenge in catalyst design and consistently produces high-perf...
Image: Phys.org
A computational method combining generative AI with atomistic simulations can identify promising platinum alloy catalyst structures for hydrogen fuel cells, report researchers from Science Tokyo. Their approach addresses a longstanding challenge in catalyst design and consistently produces high-performing candidates from several material combinations.
Originally published at Phys.org
