AI-based evolution: green hydrogen production enhances with platinum-free electrode materials

A research team at NIMS Japan has pioneered an AI technique capable of rapidly identifying materials with optimal characteristics for green hydrogen production. By leveraging this technology, the team successfully uncovered water electrolyzer electrode materials devoid of platinum-group elements—previously deemed indispensable. This discovery holds the potential to drive down the costs associated with large-scale green hydrogen production, paving the way for a sustainable energy future.

Current methods of green hydrogen production rely heavily on platinum-group elements, posing challenges due to their scarcity and high cost. To overcome this hurdle, researchers are exploring alternative, platinum-free electrode materials composed of more abundant chemical elements. However, the sheer volume of potential material combinations makes traditional evaluation methods impractical.

NIMS researchers developed an AI technique capable of swiftly predicting materials' compositions with desired properties. By adapting prediction models based on dataset sizes, the team expedited the identification process. Remarkably, they identified effective electrode materials from thousands of candidates in just one month—a task that would have taken years through manual evaluation. These materials, comprising elements like manganese, iron, and nickel, demonstrate superior electrochemical properties compared to conventional options.

The success of this AI-driven approach showcases its potential to augment human capabilities and accelerate material discovery. With plans to further optimize electrode materials, the research team aims to enhance the efficiency of electrochemical devices crucial for achieving carbon neutrality.

COMPAMED-tradefair.com; Source: National Institute for Materials Science (NIMS), Japan