Machine learning potentials for hydrogen absorption in TiCr2 Laves phases

The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCr 2 H x Laves phases is investigated for 0 < x ≤ 6 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 α phases at 0 K are predicted to be x = 1.0 and x = 1.5 for the C15 and the C14 phases, respectively. At these concentrations, C15 TiCr 2 H shows the C c monoclinic symmetry, while C14 TiCr 2 H 1.5 shows the A m a 2 orthorhombic symmetry, both of which have not been reported for this system. The first and the second hydride phases, i.e., β and β ′ , at 0 K are found around x = 3 and x = 4, respectively, for both the C15 and the C14 phases. In the second-hydride β ′ phases, C15 TiCr 2 H 4 shows the I 4 1 / a tetragonal symmetry, while C14 TiCr 2 H 4 shows the R 3 ̄ c rhombohedral symmetry. Hydrogen repulsions are found to extend to edge-sharing interstices, affecting the hydrogen ordering. Furthermore, the 6 h 2 A 2 B 2 interstices are found to be energetically substantially more preferable for C14 TiCr 2 H x than the other A 2 B 2 interstices at low hydrogen concentrations, influencing the hydrogen-occupation trend.