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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