Machine Learning Potentials for Hydrogen Absorption in TiCr Laves Phases
arXiv:2503.22824 · doi:10.1016/j.actamat.2025.121319
Abstract
The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCrH Laves phases is investigated for with density functional theory (DFT) and machine learning interatomic potentials (MLIPs). The MLIPs are trained with configurations generated through a series of active-learning schemes. Basin-hopping Monte Carlo (BHMC) simulations based on the MLIPs predict minimum-energy hydrogen configurations, along with enthalpies of formation and hydrogen orderings. The obtained phase transformations at 0 K agree well with the experiments at low temperatures. The hydrogen solubility limits in the low-concentration phases at 0 K are predicted to be and for the C15 and the C14 phases, respectively. At these concentrations, C15 TiCrH shows the monoclinic symmetry, while C14 TiCrH shows the orthorhombic symmetry, both of which have not been reported for this system. The first and the second hydride phases, i.e., and $β'$, at 0 K are found around and , respectively, for both the C15 and the C14 phases. In the second-hydride $β'$ phases, C15 TiCrH shows the tetragonal symmetry, while C14 TiCrH shows the rhombohedral symmetry. Hydrogen repulsion are found to extend to edge-sharing interstices, affecting the hydrogen ordering. Furthermore, the AB interstices are found to be energetically substantially more preferable for C14 TiCrH than the other AB interstices at low hydrogen concentrations, influencing the hydrogen-occupation trend.