Dataset

ANI-Al_NC2021-train


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Name :
ANI-Al_NC2021-train
Extended ID :
ANI-Al_NC2021-train__Smith-Nebgen-Mathew-Chen-Lubbers-Burakovsky-Tretiak-Nam-Germann-Fensin-Barros__DS_tz8gsj3xi2g4_0
ColabFit ID :
DS_tz8gsj3xi2g4_0
Files :
colabfitspec.json
Description :
Approximately 2800 configurations from a train dataset–one of a pair of train/test datasets of aluminum in crystal and melt phases, used for training and testing an ANI neural network model.
Authors :
Justin S. Smith, Benjamin Nebgen, Nithin Mathew, Jie Chen, Nicholas Lubbers, Leonid Burakovsky, Sergei Tretiak, Hai Ah Nam, Timothy Germann, Saryu Fensin, Kipton Barros
DOI :
10.60732/af254882 https://commons.datacite.org/doi.org/10.60732/af254882 https://doi.datacite.org/dois/10.60732%2Faf254882 https://doi.org/10.60732/af254882 Cite as: Smith, J. S., Nebgen, B., Mathew, N., Chen, J., Lubbers, N., Burakovsky, L., Tretiak, S., Nam, H. A., Germann, T., Fensin, S., and Barros, K. "ANI-Al NC2021-train." ColabFit, 2023. https://doi.org/10.60732/af254882.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
2,779
Num. Atoms :
363,129
Downloads :
22
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
Al (100.0%)
Methods :
DFT-PBE
Software :
Quantum ESPRESSO
Publication Link :
https://doi.org/10.1038/s41467-021-21376-0
Data Source Link :
https://github.com/atomistic-ml/ani-al
Configuration Sets by Name :
Configuration Sets by ID :
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