Plastic Heterogeneity Data of CuZr/AlSm/NiNb/FeP Metallic Glasses

This group of datasets contain the atomic-scale plastic heterogeneity data of a series of Cu-Zr (Cu₆₅Zr₃₅, Cu₅₀Zr₅₀, Cu₈₀Zr₂₀), Al₉₀Sm₁₀, Ni₆₂Nb₃₈ and Fe₈₀P₂₀ metallic glasses (in CSV format). In particular, a row of each CSV file corresponds to an atom, and includes the following information:

• ["id"] atom id;
• ["type"] atom type;
• ["x"] coordinate x of the atom in the undeformed, quenched configuration;
• ["y"] coordinate y of the atom in the undeformed, quenched configuration;
• ["z"] coordinate z of the atom in the undeformed, quenched configuration;
• ["nonaffine_displacement"] non-affine displacement of the atom at a compressive strain of 4.0% with reference to the original quenched configuration;
• ["note"] denotes whether the atom is within the two compressive ends ("compr_ends") or close to the boundary ("bds"). After featurization, these atomic data could be eliminated from later machine learning.

We simulate liquid melt quenching and deformation of Cu₆₅Zr₃₅, Cu₅₀Zr₅₀, Cu₈₀Zr₂₀, Ni₆₂Nb₃₈, Al₉₀Sm₁₀ and Fe₈₀P₂₀ metallic glasses using molecular dynamics simulations. We use 3 quenching rates of 5 × 10¹⁰, 5 × 10¹¹ and 5 × 10¹² K s^-1 for Cu-Zr metallic glasses, and 5 × 10¹⁰ K s^-1 for the other metallic glasses. We construct 3 large slab samples for each Cu-Zr glass, each of which contains 345600 atoms with dimensions ~120 (X) × 24 (Y) ×240 (Z) ų. Data from 2 glass samples are concatenated, equally undersampled and used in 5-fold cross-validation training the ML models, whereas the remaining sample is set-aside for rigorous generalization tests. For Ni₆₂Nb₃₈, Al₉₀Sm₁₀ and Fe₈₀P₂₀ metallic glasses, we construct samples of 131072 atoms. The timestep is 1 fs. During simulation, the initial configuration is built by randomly substituting into an fcc (Cu-Zr, N_i62Nb₃₈ and Al₉₀Sm₁₀) or bcc (Fe₈₀P₂₀) lattice. The samples are annealed at 2000 K for 1 ns, quenched to 50 K with each quenching rate, and relaxed at 50 K for 1 ns.

After quenching, the Cu-Zr MGs are compressed along Z axis under a strain rate of 2.5 × 10⁷ s^-1 in a quasi-static mode (constantly apply a small strain and then relax, up to the strain of 10%) at a low temperature of 50 K (see Supplementary Figure 3 for typical stress-strain curves). Periodic boundary conditions (PBCs) are imposed in Y and Z axes and free surfaces are applied along X axis to allow shear offsets. For Ni₆₂Nb₃₈, Al₉₀Sm₁₀ and Fe₈₀P₂₀ we simulate both tensile and compressive deformation with strain rates of 2.5 × 10⁷ s^-1 and 1.0 × 10⁸ s^-1 as well as with PBCs in all directions (the data of compressive deformation under 2.5 × 10⁷ s^-1 with PBC in all directions are presented here). After feature extraction, we select atoms of ~10 - 20 Å away from the surfaces or deformation ends to construct the ML datasets. We analyze non-affine displacement D² of each atom at a strain of 4.0% with reference to the undeformed configuration as a signature of plastic heterogeneity. Please see more details of D² in ML Falk, Phys. Rev. E 57, 7192-7205 (1998).

Note on data source

This data is part of our paper:

Qi Wang, Anubhav Jain. A transferable machine-learning framework linking interstice distribution and plastic heterogeneity in metallic glasses. Nature Communications 10, 5537 (2019). https://doi.org/10.1038/s41467-019-13511-9.

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