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: O. Lenchuk, J. Rohrer, and K. Albe (2024), "Mo-Si Alloys Studied by Atomistic Computer Simulations Using a Novel Machine‐Learning Interatomic Potential: Thermodynamics and Interface Phenomena", Advanced Engineering Materials26(17). DOI: 10.1002/adem.202302043.
Abstract: A machine-learning interatomic potential for Mo-Si alloys based on the atomic cluster expansion formalism is presented, its performance is validated, and it is applied for studying interface phenomena. Structural parameters, elastic constants, and melting temperatures of the crystalline body-centered cubic Mo, diamond Si, and stable Mo-Si alloys (Mo3Si, Mo5Si3, and MoSi2) are calculated and compared to experimental values. Using the trained potential defect, formation energies are calculated and the thermodynamic stability of various MoxSiy alloys is discussed with focus on Mo3Si. Finally, the intermixing between Mo and Si phases is studied by performing interface simulations of Mo|Si. The crystallization behavior of the Mo3Si phase provides additional evidence for the off-stoichiometric composition of this intermetallic phase.
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 was pulled from the paper and contains training and testing data. File(s):