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cond-mat.mtrl-sci2026
Assessing the Transferability of General-Purpose MachineLearning Interatomic Potentials for Heterogeneous Catalysis with HetCat26
Alexandre Peuch, Giaan Kler-Young, Kaifeng Niu +4
Foundation machine learning interatomic potentials (MLIPs) promise near-density functional theory (DFT) accuracy across broad areas of chemistry and materials science. However, the…
physics.chem-ph2026
Breaking Water at Graphene Defects
Samuel G. H. Brookes, IniOluwa C. Popoola, Fabian Berger +3
Water dissociation at solid surfaces underpins processes ranging from corrosion and catalysis to electrochemistry and photovoltaics. Defects often serve as reactive sites for disso…