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: B. Zhang, E. Chen, and M. Asta (2025), "Oxygen grain-boundary segregation in HCP Ti - Computational investigations using an atomic cluster expansion potential", Computational Materials Science248, 113577. DOI: 10.1016/j.commatsci.2024.113577.
Abstract: The segregation energy of oxygen interstitial solutes to grain boundaries (GBs) in hexagonal close-packed (HCP) titanium is investigated through atomistic simulations based on a machine-learning interatomic potential (MLIP). The Ti-O MLIP is developed for titanium with interstitial oxygen solutes up to a concentration of 20 at.%. It is based on the formalism of the atomic cluster expansion (ACE), trained on an extensive dataset of density functional theory calculations exploring over 200,000 atomic environments for Ti and O interstitials. The ACE MLIP is used to compute oxygen GB segregation energies in 4685 different symmetric tilt GBs with [0001], [1-100] and [1-210] tilt axes. The segregation energies span a range of -0.2 eV to 2.0 eV, and over 90 % of the 4685 GBs display one or more sites with negative (attractive) segregation energies. The lowest-energy sites are found to be those with coordination numbers and Voronoi indices most similar to that of the equilibrium octahedral site in the bulk HCP Ti structure. We further explore the efficacy of crystal-graph convolutional neural network ML models for predicting segregation energies based solely on information about the local atomic environment.
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 link contains training and testing data. Note that the link listed in the paper is incorrect. File(s):