Evolution-capable AI promotes green hydrogen production using more abundant chemical elements

March 04, 2024

A research team at NIMS has developed an AI technique to speed up the discovery of materials with desirable properties by switching prediction models depending on the sizes of the datasets available for analysis, leading to the identification of high-performance water electrolyzer electrode materials free of platinum-group elements. 
Traditional water electrolyzers rely on expensive platinum-group elements, but the new AI-driven approach enables the identification of alternative materials composed of more abundant elements like manganese, iron, nickel, zinc, and silver. These materials can facilitate large-scale production of green hydrogen, a key component of achieving carbon neutrality. The AI technique significantly reduces the time and cost involved in material discovery, dramatically accelerating the search for higher-performance materials.

From: EurekAlert!