Picturing the Gap Between the Performance and US‐DOE’s Hydrogen Storage Target: A Data‐Driven Model for MgH2 Dehydrogenation

Developing solid‐state hydrogen storage materials requires a comprehensive understanding of the dehydrogenation chemistry of a solid‐state hydride. Transition state search and kinetics calculations are essential to understanding and designing high‐performance solid‐state hydrogen storage materials by filling in the knowledge gap that current experiments cannot measure. However, the ab initio analysis of these processes is expensive and time‐consuming. Searching for descriptors to accurately predict the energy barrier is urgently needed, to accelerate the prediction of hydrogen storage material properties and identify the opportunities and challenges. Herein, we develop a data‐driven model to describe and predict the dehydrogenation barriers of a typical solid‐state hydrogen storage material, MgH2, based on the combination of the crystal Hamilton population orbital of Mg‐H bond and the distance between atomic hydrogen. All the parameters in this model can be directly calculated with significantly less computational cost than conventional transition state search, so that the dehydrogenation performance of hydrogen storage materials can be predicted efficiently. Finally, we found that this model leads to excellent agreement with typical experimental measurements reported to date and provides clear design guidelines on how to propel the performance of MgH2 closer to the target set by the United States Department of Energy (US‐DOE).