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Abstract Understanding the atomistic structure and fluxionality of Pt nanoparticles under reactive conditions is essential for rational design of effective catalysts, yet their structural complexity presents a great challenge. In this work, we combine grand canonical global optimization methods and machine learning potentials to explore the atomistic landscape of nanometer‐sized (1∼2 nm) Pt nanoparticles under a pressure of hydrogen, resulting in a comprehensive library of Pt x H y nanoparticles with over one million low‐energy metastable structures. We found that hydrogen adsorption drives a size‐dependent transformation from an amorphous to a crystalline structure, leading to sharp phase transitions for smaller nanoparticles and smooth transformations for larger ones. This behavior is governed by a competition between distinct core configurations, as well as the formation of rigid and fluxional local domains, where stability is dictated by specific surface motifs at low H coverage and by the crystalline core at high H coverage. By applying this structural library for reactivity modeling of methane dehydrogenation and ethylene hydrogenation, we show a marked discrepancy between the abundance of a surface site and its catalytic contribution, indicating that the active sites are rare, structurally distinct motifs, not the most common sites.
Chen et al. (Tue,) studied this question.