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
ColabFit ID :
DS_4pbhjtu62o2d_0
Files :
colabfitspec.json
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.
Num. Configurations :
56,822
Num. Atoms :
7,629,463
Downloads :
37
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (0.09%) Cu (4.29%) H (0.09%) Li (29.82%) O (36.88%) P (14.42%) S (14.42%)
Methods :
DFT-PBE
Software :
CP2K VASP
Publication Link :
https://doi.org/10.1038/s41467-022-29939-5
Data Source Link :
https://doi.org/10.24435/materialscloud:s0-5n
Configuration Sets by Name :
Configuration Sets by ID :
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