Data-driven model rapidly predicts dehydrogenation barriers in solid-state materials

Researchers have developed a data-driven model to predict the dehydrogenation barriers of magnesium hydride (MgH2), a promising material for solid-state hydrogen storage. This advancement holds significant potential for enhancing hydrogen storage technologies, a crucial component in the transition to sustainable energy solutions.