Tl-2021-08-04-all-icsd

The current structure dataset comprises 11671 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.

Pareto optimals

Name	Time [ms] (1core/36cores)	RMSE [meV/atom]/[eV/A]	Predictions	Files
pair-1	0.012 / 0.003	182.27 / 0.2689	–	–
pair-14	0.017 / 0.038	37.843 / 0.0967	–	–
pair-27	0.018 / 0.005	14.751 / 0.0733	–	–
pair-28	0.027 / 0.007	10.981 / 0.0618	–	–
pair-29	0.039 / 0.009	9.0469 / 0.0610	–	–
pair-32	0.051 / 0.010	7.9865 / 0.0592	predictions	mlp.lammps input log
pair-33	0.069 / 0.012	7.0908 / 0.0574	predictions	mlp.lammps input log
pair-35	0.121 / 0.021	7.0794 / 0.0569	predictions	mlp.lammps input log
pair-37	0.136 / 0.018	6.6274 / 0.0560	predictions	mlp.lammps input log
pair-38	0.171 / 0.022	6.0628 / 0.0546	predictions	mlp.lammps input log
gtinv-300	0.228 / 0.023	3.7524 / 0.0271	predictions	mlp.lammps input log
gtinv-235	0.281 / 0.023	3.5426 / 0.0259	predictions	mlp.lammps input log
gtinv-170	0.282 / 0.022	3.5339 / 0.0261	predictions	mlp.lammps input log
gtinv-303	0.339 / 0.029	2.4778 / 0.0223	predictions	mlp.lammps input log
gtinv-175	0.376 / 0.031	2.3750 / 0.0212	predictions	mlp.lammps input log
gtinv-240	0.393 / 0.030	2.3750 / 0.0211	predictions	mlp.lammps input log
gtinv-312	0.472 / 0.036	2.0954 / 0.0211	predictions	mlp.lammps input log
gtinv-190	0.523 / 0.038	2.0354 / 0.0198	predictions	mlp.lammps input log
gtinv-255	0.573 / 0.040	1.9991 / 0.0197	predictions	mlp.lammps input log
gtinv-195	0.748 / 0.053	1.7952 / 0.0189	predictions	mlp.lammps input log
gtinv-260	0.787 / 0.053	1.7763 / 0.0188	predictions	mlp.lammps input log
gtinv-265	0.983 / 0.070	1.6653 / 0.0187	predictions	mlp.lammps input log
gtinv-205	1.307 / 0.088	1.6237 / 0.0190	predictions	mlp.lammps input log
gtinv-270	1.323 / 0.091	1.5689 / 0.0189	predictions	mlp.lammps input log
gtinv-342	1.775 / 0.083	1.4360 / 0.0179	predictions	mlp.lammps input log
gtinv-330	1.834 / 0.118	1.4002 / 0.0182	predictions	mlp.lammps input log
gtinv-220	1.890 / 0.117	1.3995 / 0.0174	predictions	mlp.lammps input log
gtinv-345	1.915 / 0.092	1.2764 / 0.0178	predictions	mlp.lammps input log
gtinv-319	2.928 / 0.164	1.1804 / 0.0178	predictions	mlp.lammps input log
gtinv-266	2.966 / 0.169	1.1675 / 0.0171	predictions	mlp.lammps input log
gtinv-346	3.371 / 0.155	1.0643 / 0.0167	predictions	mlp.lammps input log
gtinv-267	3.516 / 0.196	1.0594 / 0.0163	predictions	mlp.lammps input log
gtinv-354	3.661 / 0.154	1.0517 / 0.0161	predictions	mlp.lammps input log
gtinv-349	3.839 / 0.178	0.9850 / 0.0174	predictions	mlp.lammps input log
gtinv-363	4.644 / 0.209	0.9698 / 0.0165	predictions	mlp.lammps input log
gtinv-350	6.441 / 0.340	0.9213 / 0.0166	predictions	mlp.lammps input log
gtinv-287	6.946 / 0.371	0.9051 / 0.0152	predictions	mlp.lammps input log
gtinv-232	10.649 / 0.547	0.8991 / 0.0152	predictions	mlp.lammps input log
gtinv-297	10.655 / 0.543	0.8896 / 0.0151	predictions	mlp.lammps input log
gtinv-224	14.066 / 0.687	0.8657 / 0.0148	predictions	mlp.lammps input log
gtinv-289	14.825 / 0.712	0.8544 / 0.0147	predictions	mlp.lammps input log
gtinv-234	21.888 / 1.017	0.8481 / 0.0148	predictions	mlp.lammps input log
gtinv-299	22.419 / 1.031	0.8451 / 0.0148	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.