Site Selectivity Controls Reversible Hydrogen Adsorption and Release on Tife Nanoparticles: An Interpretable Machine Learning-Assisted Study

Site-selective hydrogen adsorption and release on TiFe nanoparticles were investigated by combining geometry optimization, adsorption energetics, charge analysis, and thermodynamic screening. Multiple adsorption motifs were considered, including Ti-top and Fe-top molecular configurations with different orientations, as well as a Ti-Fe bridge configuration leading to dissociative adsorption. The energetic hierarchy reveals that the Ti-Fe bridge site provides the strongest binding and promotes hydrogen activation, while Fe-top sites exhibit moderate adsorption strength. Charge redistribution analysis shows that molecular adsorption induces primarily Fe-localized electronic response, whereas the dissociative bridge motif triggers cooperative electronic reorganization across both Ti and Fe. To evaluate operational relevance beyond adsorption strength alone, temperature- and pressure-dependent surface coverage and desorption midpoint trends were assessed, benchmarking against practical operating constraints. An interpretable machine-learning analysis further supports these mechanistic trends by highlighting charge-transfer descriptors and the H-H activation metric as key predictors of adsorption energetics. The combined results indicate that reversible hydrogen handling is favored on Fe-centered molecular sites that balance uptake and release, while excessively strong binding at dissociative bridge sites shifts release to higher temperatures. This work provides a mechanistic link between adsorption geometry, electronic interaction strength, adsorption energetics, and desorption behavior, and identifies design principles for tuning TiFe-based nanostructures toward practical hydrogen applications.