Dataset

FitSNAP_Fe_NPJ_2021

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Name :

FitSNAP_Fe_NPJ_2021

Extended ID :

FitSNAP_Fe_NPJ_2021__Nikolov-Wood-Cangi-Maillet-Marinica-Thompson-Desjarlais-Tranchida__DS_ej5u0tuycoph_0

ColabFit ID :

DS_ej5u0tuycoph_0

Files :

colabfitspec.json

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.

Authors :

Svetoslav Nikolov, Mitchell A. Wood, Attila Cangi, Jean-Bernard Maillet, Mihai-Cosmin Marinica, Aidan P. Thompson, Michael P. Desjarlais, Julien Tranchida

DOI :

10.60732/fe28ef5e https://commons.datacite.org/doi.org/10.60732/fe28ef5e https://doi.datacite.org/dois/10.60732%2Ffe28ef5e https://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.
For other citation formats, see the DataCite Fabrica page for this dataset.

Num. Configurations :

2,157

Num. Atoms :

44,480

Downloads :

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

Configuration Sets by Name :

Configuration Sets by ID :

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