Ge-2021-08-04-all-icsd

The current structure dataset comprises 13325 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

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.

Ge-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-14	0.017 / 0.038	73.269 / 0.2330	–	–
pair-27	0.018 / 0.005	28.342 / 0.1637	–	–
pair-28	0.027 / 0.007	26.707 / 0.1660	–	–
pair-31	0.050 / 0.007	23.740 / 0.1559	–	–
pair-32	0.051 / 0.010	23.660 / 0.1549	–	–
pair-33	0.069 / 0.012	22.145 / 0.1504	–	–
pair-37	0.136 / 0.018	19.623 / 0.1405	–	–
gtinv-300	0.228 / 0.023	11.387 / 0.0807	–	–
gtinv-235	0.281 / 0.023	9.8064 / 0.0717	predictions	mlp.lammps input log
gtinv-175	0.376 / 0.031	9.7406 / 0.0734	predictions	mlp.lammps input log
gtinv-240	0.393 / 0.030	9.4340 / 0.0724	predictions	mlp.lammps input log
gtinv-312	0.472 / 0.036	8.4679 / 0.0725	predictions	mlp.lammps input log
gtinv-190	0.523 / 0.038	7.5332 / 0.0665	predictions	mlp.lammps input log
gtinv-255	0.573 / 0.040	7.2238 / 0.0650	predictions	mlp.lammps input log
gtinv-236	0.804 / 0.059	6.3391 / 0.0654	predictions	mlp.lammps input log
gtinv-176	1.108 / 0.075	6.2910 / 0.0673	predictions	mlp.lammps input log
gtinv-241	1.126 / 0.076	5.9713 / 0.0652	predictions	mlp.lammps input log
gtinv-172	1.152 / 0.075	5.5992 / 0.0668	predictions	mlp.lammps input log
gtinv-237	1.177 / 0.073	5.2381 / 0.0632	predictions	mlp.lammps input log
gtinv-242	1.506 / 0.092	5.1468 / 0.0631	predictions	mlp.lammps input log
gtinv-191	1.600 / 0.102	4.8013 / 0.0613	predictions	mlp.lammps input log
gtinv-256	1.780 / 0.109	4.6845 / 0.0598	predictions	mlp.lammps input log
gtinv-192	2.106 / 0.124	4.3299 / 0.0600	predictions	mlp.lammps input log
gtinv-257	2.164 / 0.129	4.2810 / 0.0586	predictions	mlp.lammps input log
gtinv-262	2.839 / 0.166	4.2363 / 0.0578	predictions	mlp.lammps input log
gtinv-346	3.371 / 0.155	4.1752 / 0.0594	predictions	mlp.lammps input log
gtinv-351	3.420 / 0.142	4.1158 / 0.0559	predictions	mlp.lammps input log
gtinv-194	3.908 / 0.240	3.9325 / 0.0578	predictions	mlp.lammps input log
gtinv-259	4.078 / 0.244	3.8921 / 0.0566	predictions	mlp.lammps input log
gtinv-341	4.119 / 0.255	3.8286 / 0.0550	predictions	mlp.lammps input log
gtinv-347	5.540 / 0.290	3.3497 / 0.0560	predictions	mlp.lammps input log
gtinv-223	13.159 / 0.653	3.3413 / 0.0541	predictions	mlp.lammps input log
gtinv-288	13.824 / 0.659	3.3396 / 0.0529	predictions	mlp.lammps input log
gtinv-224	14.066 / 0.687	3.2818 / 0.0533	predictions	mlp.lammps input log
gtinv-228	16.624 / 0.807	3.2515 / 0.0545	predictions	mlp.lammps input log
gtinv-229	17.857 / 0.829	3.2154 / 0.0536	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.