Run machine-learning potentials using VASP style inputs.
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Updated
Sep 1, 2026 - Python
Run machine-learning potentials using VASP style inputs.
PFP/PBE + OpenMX/PBE data for surface energies and works of adhesion at α-CoSn₃ / β-Sn and Si / α-CoSn₃ interfaces — companion to Wang, Tatsumi et al. on β-Sn orientation control via α-CoSn₃ seed layers.
Hands-on guides for materials science simulations and the surrounding dev environment.
Companion data and code for Tatsumi et al., "Comparison of Elastic Constants and Surface Energies of β-Sn from Density Functional Theory, Universal Machine Learning Potential, and Empirical Potentials" (Modell. Simul. Mater. Sci. Eng., 2026) — OpenMX DFT, PFP v8/Matlantis, and MEAM/LAMMPS inputs, outputs, and analysis scripts.
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