DIVE multi-agent workflow streamlines hydrogen storage materials discovery

Developing new materials can involve a dizzying amount of trial and error for different configurations and elements. Artificial intelligence (AI) has seen a surge of popularity in energy materials research for its potential to streamline this time-consuming process. However, fully autonomous workflows that connect high-precision experimental knowledge to the discovery of credible new energy-related materials remain at an early stage.