Numerical modeling of hydrogen absorption in metal hydrides

One of the main challenges to fully utilize hydrogen as a green and renewable energy vector is its storage. We study the absorption of hydrogen in ternary compounds of type M-Mg-Ni with a combination of ab initio molecular dynamics [1] and classical molecular dynamics [2] using machine learning interatomic potentials (MLIP). Our goal is to accurately predict the enthalpy of absorption, the desorption temperature and the entropy of absorption. We employ the newly developed Machine Learning Assisted Canonical Sampling (MLACS) method [3] to generate on-the-fly interatomic potentials throughout the molecular dynamics simulation. This approach allows us to compute the phonon spectrum of the materials taking into account the anharmonicity of the potential at a reduced computational cost. We will present preliminary results to evaluate the accuracy and speedup enabled by this approach.

[1]. Gonze, X. et al. (2020). Comput. Phys. Commun. 248, 107042

[2]. Thompson, A. (2022). Comp. Phys. Commun. 271, 10817

[3]. Castellano, A. et al. (2022) Phys. Rev. B 106, L161110