Os-2021-08-25-all-icsd

../../_images/pareto244.png

The current structure dataset comprises 10919 structures generated from unique ICSD prototype structures composed of single elements with zero oxidation state. A more detailed procedure is found in Phys. Rev. B 99, 214108 (2019). The procedure to estimate interatomic potentials from the dataset is found in Phys. Rev. B 99, 214108 (2019) and Phys. Rev. B 102, 174104 (2020).

Improvement from **-dataset-10000-all-icsd

  • More robust for structures with a small interatomic distance

  • More robust for structures with a large interatomic distance

  • More complex potential models are included.

  • MLPs are estimated without using DFT stress tensors.

  • MLPs are estimated by using small regression weights for energetically unstable structures.

Predictions using Pareto optimal MLPs

../../_images/prediction-ecoh-volume138.png

The cohesive energy and volume are obtained by performing a local structure optimization from the DFT equilibrium structure. In addition, the DFT equilibrium structure is obtained by optimizing a prototype structure included in ICSD, and the prototype is used as the structure legend in the figure. Therefore, the structure type of the converged structure is sometimes different from that shown in the legend even if the potential energy surface predicted by MLP is almost the same as the true one.

The other properties predicted by each Pareto optimal MLP are available from column Predictions in the following table.

Os-2021-08-25-all-icsd shows large prediction errors. They should be carefully used. Such an MLP is often accurate for reasonable structures, but it is not accurate for unrealistic structures.

Pareto optimals

Name

Time [ms] (1core/36cores)

RMSE [meV/atom]/[eV/A]

Predictions

Files

pair-1

0.012 / 0.003

402.86 / 1.3202

pair-14

0.017 / 0.038

135.32 / 0.5788

pair-27

0.018 / 0.005

118.11 / 0.5524

pair-28

0.027 / 0.007

116.81 / 0.5626

pair-18

0.033 / 0.017

88.582 / 0.5859

pair-31

0.050 / 0.007

75.217 / 0.5222

pair-37

0.136 / 0.018

60.489 / 0.4804

gtinv-300

0.228 / 0.023

32.551 / 0.2721

gtinv-235

0.281 / 0.023

26.991 / 0.2512

gtinv-170

0.282 / 0.022

26.925 / 0.2518

gtinv-312

0.472 / 0.036

19.319 / 0.2458

gtinv-190

0.523 / 0.038

18.112 / 0.2306

gtinv-301

0.743 / 0.062

14.847 / 0.2107

gtinv-236

0.804 / 0.059

14.204 / 0.2017

gtinv-171

0.818 / 0.060

14.127 / 0.2021

gtinv-176

1.108 / 0.075

13.923 / 0.2079

gtinv-241

1.126 / 0.076

13.921 / 0.2076

gtinv-172

1.152 / 0.075

10.015 / 0.1818

gtinv-177

1.475 / 0.092

9.7844 / 0.1869

predictions

mlp.lammps input log

gtinv-191

1.600 / 0.102

9.5771 / 0.1816

predictions

mlp.lammps input log

gtinv-256

1.780 / 0.109

9.3693 / 0.1792

predictions

mlp.lammps input log

gtinv-174

1.973 / 0.134

7.6676 / 0.1635

predictions

mlp.lammps input log

gtinv-192

2.106 / 0.124

7.2682 / 0.1633

predictions

mlp.lammps input log

gtinv-179

2.634 / 0.168

6.8532 / 0.1663

predictions

mlp.lammps input log

gtinv-193

3.465 / 0.217

6.4262 / 0.1617

predictions

mlp.lammps input log

gtinv-258

3.556 / 0.220

6.4226 / 0.1602

predictions

mlp.lammps input log

gtinv-194

3.908 / 0.240

5.0339 / 0.1483

predictions

mlp.lammps input log

gtinv-209

8.915 / 0.479

4.9258 / 0.1583

predictions

mlp.lammps input log

gtinv-332

13.113 / 0.653

4.8920 / 0.1596

predictions

mlp.lammps input log

gtinv-223

13.159 / 0.653

4.5420 / 0.1524

predictions

mlp.lammps input log

gtinv-224

14.066 / 0.687

3.8601 / 0.1415

predictions

mlp.lammps input log

Column “Time” shows the time required to compute the energy and forces for 1 MD step and 1 atom, which is estimated from a simulation of 10 runs for a structure with 284 atoms using a workstation with Intel(R) Xeon(R) CPU E5-2695 v4 @ 2.10GHz. Note that the MLPs should be carefully used for extreme structures. The MLPs often return meaningless values for them.

  • All Pareto optimal MLPs are available here.