Be-2021-08-04-all-icsd

../../_images/pareto224.png

The current structure dataset comprises 13855 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-volume118.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.

Be-2021-08-04-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

24.735 / 0.2075

pair-31

0.050 / 0.007

19.581 / 0.1930

pair-32

0.051 / 0.010

18.553 / 0.1958

pair-33

0.069 / 0.012

17.491 / 0.1960

pair-37

0.136 / 0.018

14.654 / 0.1846

gtinv-300

0.228 / 0.023

11.844 / 0.0994

gtinv-235

0.281 / 0.023

10.636 / 0.0872

gtinv-312

0.472 / 0.036

8.3595 / 0.0861

predictions

mlp.lammps input log

gtinv-190

0.523 / 0.038

7.5505 / 0.0790

predictions

mlp.lammps input log

gtinv-255

0.573 / 0.040

7.4886 / 0.0773

predictions

mlp.lammps input log

gtinv-236

0.804 / 0.059

6.9605 / 0.0784

predictions

mlp.lammps input log

gtinv-172

1.152 / 0.075

6.5543 / 0.0762

predictions

mlp.lammps input log

gtinv-237

1.177 / 0.073

6.4176 / 0.0750

predictions

mlp.lammps input log

gtinv-313

1.590 / 0.102

5.6721 / 0.0734

predictions

mlp.lammps input log

gtinv-191

1.600 / 0.102

5.3533 / 0.0690

predictions

mlp.lammps input log

gtinv-256

1.780 / 0.109

5.2578 / 0.0677

predictions

mlp.lammps input log

gtinv-192

2.106 / 0.124

4.8727 / 0.0662

predictions

mlp.lammps input log

gtinv-257

2.164 / 0.129

4.8244 / 0.0652

predictions

mlp.lammps input log

gtinv-193

3.465 / 0.217

4.4264 / 0.0648

predictions

mlp.lammps input log

gtinv-258

3.556 / 0.220

4.3116 / 0.0635

predictions

mlp.lammps input log

gtinv-194

3.908 / 0.240

4.2085 / 0.0627

predictions

mlp.lammps input log

gtinv-259

4.078 / 0.244

4.1171 / 0.0615

predictions

mlp.lammps input log

gtinv-332

13.113 / 0.653

3.8264 / 0.0646

predictions

mlp.lammps input log

gtinv-223

13.159 / 0.653

3.6793 / 0.0612

predictions

mlp.lammps input log

gtinv-288

13.824 / 0.659

3.6109 / 0.0599

predictions

mlp.lammps input log

gtinv-224

14.066 / 0.687

3.5384 / 0.0593

predictions

mlp.lammps input log

gtinv-289

14.825 / 0.712

3.4908 / 0.0583

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.