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 |
| 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. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
C (1.17%) H (1.65%) In (38.38%) O (58.76%) Pt (0.04%) |
| Number of Configurations | 1,994 |
| Number of Atoms | 163,746 |
| Links |
https://doi.org/10.5281/zenodo.8268726 https://doi.org/10.48550/arXiv.2301.09931 |
| Configuration Sets by Name |
COHInPt_schaaf_2023_dopant-configs — dopant-configs molecular dynamics data from COHInPt_schaaf_2023 set COHInPt_schaaf_2023_Pt_doped_training — Pt_doped_training molecular dynamics data from COHInPt_schaaf_2023 set COHInPt_schaaf_2023_undoped_training — undoped_training molecular dynamics data from COHInPt_schaaf_2023 set COHInPt_schaaf_2023_bi-HCOO_D — bi-HCOO_D molecular dynamics data from COHInPt_schaaf_2023 set COHInPt_schaaf_2023_dft-intermediates — dft-intermediates molecular dynamics data from COHInPt_schaaf_2023 set |
| Configuration Sets by ID |
CS_cobd92vzjnug_0 CS_cx8bji6p453o_0 CS_hcoijaf5nw65_0 CS_w8piu86pb8kw_0 CS_wqzuqhngwymc_0 |
| Calculated Properties | |
| ColabFit ID | DS_l9f0rjjqfd67_0 |
| Files | colabfitspec.json |
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