Re-2021-08-25-all-icsd

../../_images/pareto250.png

The current structure dataset comprises 11476 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-volume144.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.

Re-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-27

0.018 / 0.005

64.651 / 0.3883

pair-28

0.027 / 0.007

62.756 / 0.3890

pair-31

0.050 / 0.007

47.079 / 0.3740

pair-37

0.136 / 0.018

35.022 / 0.3492

gtinv-300

0.228 / 0.023

28.635 / 0.2537

gtinv-175

0.376 / 0.031

26.636 / 0.2511

gtinv-240

0.393 / 0.030

26.595 / 0.2506

gtinv-312

0.472 / 0.036

17.881 / 0.2318

gtinv-172

1.152 / 0.075

14.100 / 0.1934

gtinv-237

1.177 / 0.073

14.038 / 0.1929

gtinv-177

1.475 / 0.092

12.846 / 0.1938

gtinv-242

1.506 / 0.092

12.807 / 0.1936

gtinv-302

1.579 / 0.111

12.120 / 0.1947

gtinv-174

1.973 / 0.134

9.8866 / 0.1784

predictions

mlp.lammps input log

gtinv-239

2.057 / 0.133

9.8503 / 0.1780

predictions

mlp.lammps input log

gtinv-192

2.106 / 0.124

9.0973 / 0.1762

predictions

mlp.lammps input log

gtinv-179

2.634 / 0.168

8.9261 / 0.1808

predictions

mlp.lammps input log

gtinv-244

2.680 / 0.171

8.9106 / 0.1806

predictions

mlp.lammps input log

gtinv-193

3.465 / 0.217

8.4831 / 0.1774

predictions

mlp.lammps input log

gtinv-258

3.556 / 0.220

8.4398 / 0.1772

predictions

mlp.lammps input log

gtinv-194

3.908 / 0.240

6.8220 / 0.1664

predictions

mlp.lammps input log

gtinv-259

4.078 / 0.244

6.8086 / 0.1662

predictions

mlp.lammps input log

gtinv-269

6.917 / 0.387

6.7674 / 0.1709

predictions

mlp.lammps input log

gtinv-332

13.113 / 0.653

6.2937 / 0.1719

predictions

mlp.lammps input log

gtinv-223

13.159 / 0.653

6.0923 / 0.1682

predictions

mlp.lammps input log

gtinv-288

13.824 / 0.659

6.0588 / 0.1680

predictions

mlp.lammps input log

gtinv-224

14.066 / 0.687

5.0846 / 0.1588

predictions

mlp.lammps input log

gtinv-289

14.825 / 0.712

5.0771 / 0.1586

predictions

mlp.lammps input log

gtinv-294

17.107 / 0.825

4.9651 / 0.1610

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.