Dataset

Silica_NPJCM_2022

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Name :

Silica_NPJCM_2022

Extended ID :

Silica_NPJCM_2022__Erhard-Rohrer-Albe-Deringer__DS_14m394gnh3ae_0

ColabFit ID :

DS_14m394gnh3ae_0

Files :

colabfitspec.json

Description :

This dataset was created for the purpose of training an MLIP for silica (SiO2). For initial DFT computations, GPAW (in combination with ASE) was used with LDA, PBE and PBEsol functionals; and VASP with the SCAN functional. All calculations used the projector augmented-wave method. After comparison, it was found that SCAN performed best, and all values were recalculated using SCAN. An energy cut-off of 900 eV and a k-spacing of 0.23 Å-1 were used.

Authors :

Linus C. Erhard, Jochen Rohrer, Karsten Albe, Volker L. Deringer

DOI :

10.60732/c2bee5fa https://commons.datacite.org/doi.org/10.60732/c2bee5fa https://doi.datacite.org/dois/10.60732%2Fc2bee5fa https://doi.org/10.60732/c2bee5fa Cite as: Erhard, L. C., Rohrer, J., Albe, K., and Deringer, V. L. "Silica NPJCM 2022." ColabFit, 2023. https://doi.org/10.60732/c2bee5fa.
For other citation formats, see the DataCite Fabrica page for this dataset.

Num. Configurations :

3,074

Num. Atoms :

268,118

Downloads :

Calculated Property Types :

atomic_forces cauchy_stress energy

Elements :

O (66.47%) Si (33.53%)

Methods :

DFT-SCAN

Software :

VASP

Publication Link :

https://doi.org/10.1038/s41524-022-00768-w

Data Source Link :

https://doi.org/10.5281/zenodo.6353683

Configuration Sets by Name :

Configuration Sets by ID :

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