2 papers
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…
cond-mat.mtrl-sci2014
Controlling the electronic structure of graphene using surface-adsorbate interactions
Piotr Matyba, Adra V. Carr, Cong Chen +8
We show that strong coupling between graphene and the substrate is mitigated when 0.8 monolayer of Na is adsorbed and consolidated on top graphene-on-Ni(111). Specifically, the π s…