Dataset

COHInPt_schaaf_2023


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Name :
COHInPt_schaaf_2023
Extended ID :
COHInPt_schaaf_2023__Schaaf-Fako-De-Schafer-Csanyi__DS_l9f0rjjqfd67_0
ColabFit ID :
DS_l9f0rjjqfd67_0
Files :
colabfitspec.json
Description :
Training and simulation data from machine learning force field model applied to steps of the hydrogenation of carbon dioxide to methanol over an indium oxide catalyst, with and without platinum doping.
Authors :
Lars Schaaf, Edvin Fako, Sandip De, Ansgar Schafer, Gabor Csanyi
DOI :
10.60732/d16f9667 https://commons.datacite.org/doi.org/10.60732/d16f9667 https://doi.datacite.org/dois/10.60732%2Fd16f9667 https://doi.org/10.60732/d16f9667 Cite as: Schaaf, L., Fako, E., De, S., Schafer, A., and Csanyi, G. "COHInPt schaaf 2023." ColabFit, 2023. https://doi.org/10.60732/d16f9667.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
1,994
Num. Atoms :
163,746
Downloads :
31
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (1.17%) H (1.65%) In (38.38%) O (58.76%) Pt (0.04%)
Methods :
DFT-PBE
Software :
Quantum ESPRESSO
Publication Link :
https://doi.org/10.1038/s41524-023-01124-2
Data Source Link :
https://doi.org/10.5281/zenodo.8268726
Other Links :
https://doi.org/10.48550/arXiv.2301.09931
Configuration Sets by Name :
Configuration Sets by ID :
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