Dataset

FitSNAP_Fe_NPJ_2021


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Species content of dataset


Name :
FitSNAP_Fe_NPJ_2021
Authors :
Svetoslav Nikolov, Mitchell A. Wood, Attila Cangi, Jean-Bernard Maillet, Mihai-Cosmin Marinica, Aidan P. Thompson, Michael P. Desjarlais, Julien Tranchida
Description :
About 2,500 configurations of alpha-Fe used in the training and testing of a ML model with the goal of building magneto-elastic machine-learning interatomic potentials for large-scale spin-lattice dynamics simulations.
DOI :
https://doi.org/10.60732/fe28ef5e https://commons.datacite.org/doi.org/10.60732/fe28ef5e
Cite As :
Nikolov, S., Wood, M. A., Cangi, A., Maillet, J., Marinica, M., Thompson, A. P., Desjarlais, M. P., and Tranchida, J. "FitSNAP Fe NPJ 2021." ColabFit, 2023. https://doi.org/10.60732/fe28ef5e.
ColabFit ID :
DS_ej5u0tuycoph_0
Extended ID :
FitSNAP_Fe_NPJ_2021__Nikolov-Wood-Cangi-Maillet-Marinica-Thompson-Desjarlais-Tranchida__DS_ej5u0tuycoph_0
Date Added :
2023-06-30
License :
GPL-2.0-only
Downloads :
26
Num. Configurations :
2,157
Num. Atoms :
44,480
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
Fe (100.0%)
Methods :
DFT-PBE
Software :
VASP
Publication Link :
https://doi.org/10.1038/s41524-021-00617-2
Data Source Link :
https://github.com/FitSNAP
Spec File :
colabfitspec.json
Configuration Sets by Name :
Configuration Sets by ID :
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