Dataset

JARVIS_ALIGNN_FF

Download Original Data Files 57.5 MB

Download Dataset Parquet Files 214.0 MB

Species content of dataset

Name :

JARVIS_ALIGNN_FF

Extended ID :

JARVIS_ALIGNN_FF__Choudhary-DeCost-Major-Butler-Thiyagalingam-Tavazza__DS_720rbshv96l1_0

ColabFit ID :

DS_720rbshv96l1_0

Files :

colabfitspec.json

Description :

The JARVIS_ALIGNN_FF dataset is part of the joint automated repository for various integrated simulations (JARVIS) database. This dataset is a subset of the JARVIS DFT dataset, filtered to contain just the first, last, middle, maximum energy and minimum energy structures. Additionally, calculation run snapshots are filtered for uniqueness, and the dataset contains only perfect structures. DFT energies, stresses and forces in this dataset were used to train an atomisitic line graph neural network (ALIGNN)-based FF model. JARVIS is a set of tools and datasets built to meet current materials design challenges.

Authors :

Kamal Choudhary, Brian DeCost, Lily Major, Keith Butler, Jeyan Thiyagalingam, Francesca Tavazza

DOI :

10.60732/45deafd8 https://commons.datacite.org/doi.org/10.60732/45deafd8 https://doi.datacite.org/dois/10.60732%2F45deafd8 https://doi.org/10.60732/45deafd8 Cite as: Choudhary, K., DeCost, B., Major, L., Butler, K., Thiyagalingam, J., and Tavazza, F. "JARVIS ALIGNN FF." ColabFit, 2023. https://doi.org/10.60732/45deafd8.
For other citation formats, see the DataCite Fabrica page for this dataset.

Num. Configurations :

304,146

Num. Atoms :

3,178,329

Downloads :

Calculated Property Types :

atomic_forces cauchy_stress energy

Elements :

Ac (0.07%) Ag (0.76%) Al (1.55%) Ar (0.03%) As (0.96%) Au (0.63%) B (1.39%) Ba (1.7%) Be (1.24%) Bi (0.77%) Br (1.27%) C (2.12%) Ca (1.08%) Cd (0.62%) Ce (0.37%) Cl (2.04%) Co (1.64%) Cr (0.82%) Cs (0.0%) Cu (1.14%) Dy (0.43%) Er (0.42%) Eu (0.06%) F (5.01%) Fe (1.51%) Ga (0.87%) Gd (0.0%) Ge (1.0%) H (3.47%) He (0.01%) Hf (0.47%) Hg (0.44%) Ho (0.43%) I (1.12%) In (0.7%) Ir (0.5%) K (1.18%) Kr (0.02%) La (0.36%) Li (2.98%) Lu (0.25%) Mg (1.47%) Mn (1.73%) Mo (0.75%) N (1.95%) Na (1.45%) Nb (0.67%) Nd (0.48%) Ne (0.01%) Ni (1.32%) Np (0.06%) O (21.33%) Os (0.27%) P (1.63%) Pa (0.07%) Pb (0.52%) Pd (0.78%) Pm (0.13%) Pr (0.43%) Pt (0.61%) Pu (0.1%) Rb (0.9%) Re (0.15%) Rh (0.69%) Ru (0.51%) S (3.9%) Sb (1.04%) Sc (0.54%) Se (2.13%) Si (1.75%) Sm (0.47%) Sn (0.97%) Sr (0.86%) Ta (0.49%) Tb (0.41%) Tc (0.17%) Te (1.36%) Th (0.17%) Ti (0.94%) Tl (0.56%) Tm (0.33%) U (0.38%) V (1.18%) W (0.46%) Xe (0.02%) Y (0.62%) Yb (0.37%) Zn (0.83%) Zr (0.58%)

Methods :

IP-ALIGNN-FF

Software :

VASP

Publication Link :

https://doi.org/10.1039/D2DD00096B

Data Source Link :

https://ndownloader.figshare.com/files/38522315

Other Links :

https://github.com/usnistgov/alignn https://jarvis.nist.gov/

Configuration Sets by Name :

Configuration Sets by ID :

Name: JARVIS_ALIGNN_FF Extended ID: JARVIS_ALIGNN_FF__Choudhary-DeCost-Major-Butler-Thiyagalingam-Tavazza__DS_720rbshv96l1_0 Description: The JARVIS_ALIGNN_FF dataset is part of the joint automated repository for various integrated simulations (JARVIS) database. This dataset is a subset of the JARVIS DFT dataset, filtered to contain just the first, last, middle, maximum energy and minimum energy structures. Additionally, calculation run snapshots are filtered for uniqueness, and the dataset contains only perfect structures. DFT energies, stresses and forces in this dataset were used to train an atomisitic line graph neural network (ALIGNN)-based FF model. JARVIS is a set of tools and datasets built to meet current materials design challenges. Authors: Kamal Choudhary Brian DeCost Lily Major Keith Butler Jeyan Thiyagalingam Francesca Tavazza DOI: 10.60732/45deafd8 Calculated Property Types: atomic_forces cauchy_stress energy Elements: Ac (0.07%) Ag (0.76%) Al (1.55%) Ar (0.03%) As (0.96%) Au (0.63%) B (1.39%) Ba (1.7%) Be (1.24%) Bi (0.77%) Br (1.27%) C (2.12%) Ca (1.08%) Cd (0.62%) Ce (0.37%) Cl (2.04%) Co (1.64%) Cr (0.82%) Cs (0.0%) Cu (1.14%) Dy (0.43%) Er (0.42%) Eu (0.06%) F (5.01%) Fe (1.51%) Ga (0.87%) Gd (0.0%) Ge (1.0%) H (3.47%) He (0.01%) Hf (0.47%) Hg (0.44%) Ho (0.43%) I (1.12%) In (0.7%) Ir (0.5%) K (1.18%) Kr (0.02%) La (0.36%) Li (2.98%) Lu (0.25%) Mg (1.47%) Mn (1.73%) Mo (0.75%) N (1.95%) Na (1.45%) Nb (0.67%) Nd (0.48%) Ne (0.01%) Ni (1.32%) Np (0.06%) O (21.33%) Os (0.27%) P (1.63%) Pa (0.07%) Pb (0.52%) Pd (0.78%) Pm (0.13%) Pr (0.43%) Pt (0.61%) Pu (0.1%) Rb (0.9%) Re (0.15%) Rh (0.69%) Ru (0.51%) S (3.9%) Sb (1.04%) Sc (0.54%) Se (2.13%) Si (1.75%) Sm (0.47%) Sn (0.97%) Sr (0.86%) Ta (0.49%) Tb (0.41%) Tc (0.17%) Te (1.36%) Th (0.17%) Ti (0.94%) Tl (0.56%) Tm (0.33%) U (0.38%) V (1.18%) W (0.46%) Xe (0.02%) Y (0.62%) Yb (0.37%) Zn (0.83%) Zr (0.58%) Methods: IP-ALIGNN-FF Software: VASP Number of Configurations: 304,146 Number of Atoms: 3,178,329 Publication Link: https://doi.org/10.1039/D2DD00096B Data Source Link: https://ndownloader.figshare.com/files/38522315 Other Links: https://github.com/usnistgov/alignn https://jarvis.nist.gov/

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