Density functional theory (DFT) calculations were performed to understand the atomistic mechanisms of hydrogen absorption in selected HEA compositions. All DFT calculations were performed using the Vienna ab initio simulation package, using the same settings as those used in the SI of our previous work. Machine learning. Our models are trained on the thermodynamic data contained in v0.0.4 of the ML-HydPARK database, which includes recent literature data on high entropy alloy hydrides and metal hydrides for compression. The Magpie strategy, as implemented in Matminer, was employed for materials featurization. The set of elemental properties, p, utilized by Magpie (electronegativity, covalent radius, etc.) and the molar fractions, f , in a given composition are combined in various operations like mean (p