Run machine-learning potentials using VASP style inputs.

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., in review) — OpenMX DFT, PFP v8/Matlantis, and MEAM/LAMMPS inputs, outputs, and analysis scripts.

GRRMPYのドキュメント

Hands-on guides for materials science simulations and the surrounding dev environment.

Matlantisを使用する上で便利な機能&Blender上で機能するPythonスクリプトを作成するライブラリ

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.