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Name Silica_NPJCM_2022
Extended ID Silica_NPJCM_2022_ErhardRohrerAlbeDeringer__DS_14m394gnh3ae_0
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

Cite as: Erhard, L. C., Rohrer, J., Albe, K., and Deringer, V. L. "Silica NPJCM 2022." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements O (66.47%)
Si (33.53%)
Number of Data Objects 3,074
Number of Configurations 3,074
Number of Atoms 268,118
Configuration Sets by Name SiO2_quench_phase — SiO2 snapshots taken during the quenching process
SiO2_bulk_amorphous — SiO2 snapshot taken after equilibration of the amorphous phase.
SiO2_small_cluster — SiO2 dimers and configurations with added oxygen clusters
SiO2_bulk_crystal — SiO2 structures in crystalline phase
SiO2_liquid_phase — SiO2 snapshots taken after equilibrating the liquid phase
Configuration Sets by ID CS_1ij169zb9ncj_0
Data Objects
ColabFit ID DS_14m394gnh3ae_0
Files colabfitspec.json

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