fig9

PhyMLP: an automated strategy for machine-learning potential construction via data fusion and adaptive point-sampling

Figure 9. Validation of the machine-learned tungsten potential for dislocation core properties, lattice dynamics, and thermal behavior. (A) The core structure of a 1/2<111> screw dislocation predicted by the potential shows a non-degenerate compact configuration. The different colors of the atoms (red, green, and blue) denote three consecutive (111) atomic planes along the dislocation line; (B) Comparison of phonon dispersion curves with experimental measurements and DFT calculations; (C) Comparison of the change in the thermal expansion coefficient with temperature and experimental data. DFT: Density functional theory.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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