Al-2021-08-04-all-icsd

../../_images/pareto220.png

The current structure dataset comprises 13768 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-volume114.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.

Pareto optimals

Name

Time [ms] (1core/36cores)

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

Predictions

Files

pair-14

0.017 / 0.038

39.416 / 0.2012

pair-27

0.018 / 0.005

16.402 / 0.0992

pair-28

0.027 / 0.007

16.268 / 0.0960

pair-29

0.039 / 0.009

15.223 / 0.0961

pair-31

0.050 / 0.007

14.376 / 0.0928

pair-32

0.051 / 0.010

12.445 / 0.0884

pair-33

0.069 / 0.012

11.961 / 0.0873

pair-37

0.136 / 0.018

10.893 / 0.0835

pair-38

0.171 / 0.022

10.523 / 0.0825

gtinv-300

0.228 / 0.023

5.6872 / 0.0466

predictions

mlp.lammps input log

gtinv-235

0.281 / 0.023

4.5288 / 0.0417

predictions

mlp.lammps input log

gtinv-175

0.376 / 0.031

4.4543 / 0.0443

predictions

mlp.lammps input log

gtinv-240

0.393 / 0.030

4.3622 / 0.0436

predictions

mlp.lammps input log

gtinv-312

0.472 / 0.036

3.7889 / 0.0410

predictions

mlp.lammps input log

gtinv-190

0.523 / 0.038

2.9882 / 0.0362

predictions

mlp.lammps input log

gtinv-255

0.573 / 0.040

2.9755 / 0.0356

predictions

mlp.lammps input log

gtinv-172

1.152 / 0.075

2.7433 / 0.0374

predictions

mlp.lammps input log

gtinv-237

1.177 / 0.073

2.7210 / 0.0369

predictions

mlp.lammps input log

gtinv-177

1.475 / 0.092

2.6711 / 0.0372

predictions

mlp.lammps input log

gtinv-242

1.506 / 0.092

2.6349 / 0.0369

predictions

mlp.lammps input log

gtinv-191

1.600 / 0.102

2.3833 / 0.0348

predictions

mlp.lammps input log

gtinv-256

1.780 / 0.109

2.3805 / 0.0343

predictions

mlp.lammps input log

gtinv-220

1.890 / 0.117

2.1440 / 0.0335

predictions

mlp.lammps input log

gtinv-192

2.106 / 0.124

2.0907 / 0.0339

predictions

mlp.lammps input log

gtinv-257

2.164 / 0.129

2.0732 / 0.0334

predictions

mlp.lammps input log

gtinv-340

2.596 / 0.116

2.0660 / 0.0316

predictions

mlp.lammps input log

gtinv-197

2.819 / 0.158

1.9705 / 0.0330

predictions

mlp.lammps input log

gtinv-262

2.839 / 0.166

1.9371 / 0.0326

predictions

mlp.lammps input log

gtinv-193

3.465 / 0.217

1.8309 / 0.0322

predictions

mlp.lammps input log

gtinv-258

3.556 / 0.220

1.8034 / 0.0317

predictions

mlp.lammps input log

gtinv-259

4.078 / 0.244

1.7920 / 0.0322

predictions

mlp.lammps input log

gtinv-344

4.588 / 0.248

1.7849 / 0.0321

predictions

mlp.lammps input log

gtinv-263

4.878 / 0.289

1.7809 / 0.0321

predictions

mlp.lammps input log

gtinv-264

5.489 / 0.315

1.6220 / 0.0312

predictions

mlp.lammps input log

gtinv-286

6.000 / 0.346

1.5499 / 0.0302

predictions

mlp.lammps input log

gtinv-287

6.946 / 0.371

1.4590 / 0.0295

predictions

mlp.lammps input log

gtinv-288

13.824 / 0.659

1.4049 / 0.0294

predictions

mlp.lammps input log

gtinv-224

14.066 / 0.687

1.3126 / 0.0288

predictions

mlp.lammps input log

gtinv-289

14.825 / 0.712

1.3013 / 0.0286

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.