Dataset

HDNNP_H2O


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Name :
HDNNP_H2O
Extended ID :
HDNNP_H2O__Morawietz-Behler__DS_in2572v33lon_0
ColabFit ID :
DS_in2572v33lon_0
Files :
colabfitspec.json
Description :
Approximately 28,000 configurations split into 4 datasets, each using a different functional, used in the training of a high-dimensional neural network potential (HDNNP).
Authors :
Tobias Morawietz, Jörg Behler
DOI :
10.60732/4f9f05e5 https://commons.datacite.org/doi.org/10.60732/4f9f05e5 https://doi.datacite.org/dois/10.60732%2F4f9f05e5 https://doi.org/10.60732/4f9f05e5 Cite as: Morawietz, T., and Behler, J. "HDNNP H2O." ColabFit, 2023. https://doi.org/10.60732/4f9f05e5.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
14,537
Num. Atoms :
1,523,796
Downloads :
28
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
H (66.67%) O (33.33%)
Methods :
DFT-RPBE+D3 DFT-BLYP DFT-rPBE DFT-BLYP+D3
Software :
FHI-aims
Publication Link :
https://doi.org/10.1073/pnas.1602375113
Data Source Link :
https://doi.org/10.5281/zenodo.2634097
Other Links :
https://doi.org/10.1103/PhysRevLett.98.146401
Configuration Sets by Name :
Configuration Sets by ID :
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