fig2

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

Figure 2. Comparison of the E-V relationships for various pure tungsten polymorphs calculated using the Rose EOS, first-principles DFT calculations, and trained MLP (called “Potential” in the figure). The horizontal axes represent the relative volume (V/V0), and the vertical axes represent the energy per atom (eV/atom), illustrating the structural stability under isotropic deformation. (A) BCC ground-state structure; (B) HCP structure; (C) FCC structure; (D) Diamond structure; (E) A15 structure; (F) C15 structure. E-V: Energy-volume; EOS: equation of state; DFT: density functional theory; MLP: machine-learning potential; BCC: body-centered cubic; HCP: hexagonal close-packed; FCC: face-centered cubic.

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