Dataset
NequIP_NC_2022
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| Name | NequIP_NC_2022 |
|---|---|
| Extended ID | NequIP_NC_2022__Batzner-Musaelian-Sun-Geiger-Mailoa-Kornbluth-Molinari-Smidt-Kozinsky__DS_4pbhjtu62o2d_0 |
| Description | Approximately 57,000 configurations from the evaluation datasets for NequIP graph neural network model for interatomic potentials. Trajectories have been taken from LIPS, LIPO glass melt-quench simulation, and formate decomposition on Cu datasets. |
| Authors |
Simon Batzner Albert Musaelian Lixin Sun Mario Geiger Jonathan P. Mailoa Mordechai Kornbluth Nicola Molinari Tess E. Smidt Boris Kozinsky |
| DOI |
10.60732/e05d99fd
https://commons.datacite.org/doi.org/10.60732/e05d99fd https://doi.datacite.org/dois/10.60732%2Fe05d99fd https://doi.org/10.60732/e05d99fd Cite as: Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., Molinari, N., Smidt, T. E., and Kozinsky, B. "NequIP NC 2022." ColabFit, 2023. https://doi.org/10.60732/e05d99fd. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
C (0.09%) Cu (4.31%) H (0.09%) Li (29.81%) O (36.87%) P (14.41%) S (14.42%) |
| Number of Configurations | 56,856 |
| Number of Atoms | 7,631,075 |
| Links |
https://doi.org/10.24435/materialscloud:s0-5n https://doi.org/10.1038/s41467-022-29939-5 |
| Configuration Sets by Name |
NequIP_NC_2022_LIPS — Lithium Thiophosphate (Li6.75P3S11) configurations from NequIP_NC_2022 dataset NequIP_NC_2022_LIPO_quench — Lithium Phosphate amorphous glass (Li4P2O7) configurations from NequIP_NC_2022 dataset NequIP_NC_2022_Cu_formate — Cu-formate configurations, Cu <110> undergoing dehydrogenation decomposition, from NequIP_NC_2022 dataset |
| Configuration Sets by ID |
CS_34uj6elixnxi_0 CS_cevorpx3p7ed_0 CS_g122der0lmc1_0 |
| Calculated Properties | |
| ColabFit ID | DS_4pbhjtu62o2d_0 |
| Files | colabfitspec.json |
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