Dataset

sGDML_Benzene_DFT_NC2018




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Name :
sGDML_Benzene_DFT_NC2018
ColabFit ID :
Description :
The data used for training the DFT models were created running ab initio MD in the NVT ensemble using the Nosé-Hoover thermostat at 500 K during a 200 ps simulation with a resolution of 0.5 fs. Forces and energies were computed using all-electrons at the generalized gradient approximation level of theory with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional, treating van der Waals interactions with the Tkatchenko-Scheffler (TS) method. All calculations were performed with FHI-aims. The final training data was generated by subsampling the full trajectory under preservation of the Maxwell-Boltzmann distribution for the energies.
Authors :
Stefan Chmiela, Huziel E. Sauceda, Klaus-Robert Müller, Alexandre Tkatchenko
DOI :
10.60732/18404d62 https://commons.datacite.org/doi.org/10.60732/18404d62 https://doi.datacite.org/dois/10.60732%2F18404d62 https://doi.org/10.60732/18404d62 Cite as: Chmiela, S., Sauceda, H. E., Müller, K., and Tkatchenko, A. "sGDML Benzene DFT NC2018." ColabFit, 2023. https://doi.org/10.60732/18404d62.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
49,862
Num. Atoms :
598,344
Downloads :
32
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (50.0%) H (50.0%)
Methods :
DFT-PBE+TS
Software :
FHI-aims
Data Source Link :
Configuration Sets by Name :
Configuration Sets by ID :

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