Data-driven multi-element substitution of TiFe alloys for tunable thermodynamics and enhanced activation behaviour for hydrogen storage

TiFe alloys offer high volumetric hydrogen storage but face activation and tunability limits. Using machine learning, we propose a multi-element substitution strategy that predicts hydride stability and enables near room-temperature activation.