Calculation update! New properties have been added to the website for dislocation monopole core structures, dynamic relaxes of both crystal and liquid phases, and melting temperatures! Currently, the results for these properties predominately focus on EAM-style potentials, but the results will be updated for other potentials as the associated calculations finish. Feel free to give us feedback on the new properties so we can improve their representations as needed.
Warning! Note that elemental potentials taken from alloy descriptions may not work well for the pure species. This is particularly true if the elements were fit for compounds instead of being optimized separately. As with all interatomic potentials, please check to make sure that the performance is adequate for your problem.
Citation: A. Ngoipala, C. Schott, V. Briega‐Martos, M. Qamar, M. Mrovec, S. Javan Nikkhah, T.O. Schmidt, L. Deville, A. Capogrosso, L. Moumaneix, T. Kallio, A. Viola, F. Maillard, R. Drautz, A.S. Bandarenka, S. Cherevko, M. Vandichel, and E.L. Gubanova (2024), "Hydride‐Induced Reconstruction of Pd Electrode Surfaces: A Combined Computational and Experimental Study", Advanced Materials37(4). DOI: 10.1002/adma.202410951.
Abstract: Designing electrocatalysts with optimal activity and selectivity relies on a thorough understanding of the surface structure under reaction conditions. In this study, experimental and computational approaches are combined to elucidate reconstruction processes on low-index Pd surfaces during H-insertion following proton electroreduction. While electrochemical scanning tunneling microscopy clearly reveals pronounced surface roughening and morphological changes on Pd(111), Pd(110), and Pd(100) surfaces during cyclic voltammetry, a complementary analysis using inductively coupled plasma mass spectrometry excludes Pd dissolution as the primary cause of the observed restructuring. Large-scale molecular dynamics simulations further show that these surface alterations are related to the creation and propagation of structural defects as well as phase transformations that take place during hydride formation.
Citation: M. Qamar, A. Ngoipala, M. Mrovec, M. Vandichel, and R. Drautz (2026), "Hydride formation and phase separation in palladium nanoparticles from a transferable atomic cluster expansion potential". DOI: 10.48550/ARXIV.2606.09341.
Abstract: The palladium-hydrogen system is a prototype for hydrogen-metal interactions and underpins technologies such as hydrogen storage, catalysis and purification. Yet its nanoscale behaviour - where surface and interface energetics, elastic coherency strain and size-dependent thermodynamics govern phase separation - has eluded accurate atomistic simulation. Empirical potentials misrepresent the energetics of interstitial hydrogen, while existing machine-learning models are restricted to bulk phases at low-hydrogen environments. Here we introduce an atomic cluster expansion (ACE) for Pd-H that reproduces formation energies, phonon spectra, elastic constants, hydrogen migration barriers and surface adsorption with near-DFT accuracy, benchmarked directly against neutron-scattering, high-pressure and lattice-expansion experiments. Its near-linear scaling and CPU efficiency make molecular dynamics of PdHx nanoparticles exceeding 28,000 atoms (∼12 nm in diameter) tractable over nanosecond timescales. These simulations resolve, at the atomic scale, the kinetic separation of α- and β-PdHx into a core-shell architecture, reproduce the experimentally observed size dependence of the lattice parameter, and uncover a pronounced hydrogen-induced lowering of the nanoparticle melting temperature. The potential brings experimentally relevant scales of metal-hydride dynamics within quantitative reach.
Notes: This listing is for the ACE Pd-H model referred to as ACE_D3 in the second citation that was trained on PBE data with the D3 dispursion correction.
See Computed Properties Notes: These files were provided by Sergei Starikov on July 15, 2026. The .yaml file is the fitted potential in the original format, while the .yace file is in the LAMMPS-compatible format. The .asi file can be used with pace/extrapolation to perform additional active learning. The link was pulled from the paper and contains training and testing data, and other supporting files. File(s):