Dataset

COLL_train


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Name COLL_train
Extended ID COLL_train__Gasteiger-Giri-Margraf-Günnemann__DS_cifhpgzw3ckj_0
Description Training set from COLL. Consists of configurations taken from molecular collisions of different small organic molecules. Energies and forces for 140,000 random snapshots taken from these trajectories were recomputed with density functional theory (DFT). These calculations were performed with the revPBE functional and def2-TZVP basis, including D3 dispersion corrections
Authors Johannes Gasteiger
Shankari Giri
Johannes T. Margraf
Stephan Günnemann
DOI 10.60732/f95867ef
https://commons.datacite.org/doi.org/10.60732/f95867ef
https://doi.datacite.org/dois/10.60732%2Ff95867ef
https://doi.org/10.60732/f95867ef

Cite as: Gasteiger, J., Giri, S., Margraf, J. T., and Günnemann, S. "COLL train." ColabFit, 2023. https://doi.org/10.60732/f95867ef.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
atomization_energy
cauchy_stress
energy
Elements C (32.99%)
H (54.05%)
O (12.97%)
Number of Configurations 120,000
Number of Atoms 1,225,350
Links https://doi.org/10.6084/m9.figshare.13289165.v1
https://doi.org/10.48550/arXiv.2011.14115
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Calculated Properties
ColabFit ID DS_cifhpgzw3ckj_0
Files colabfitspec.json

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