Dataset

BOTnet_ACAC_2022_train_600K_MD




Species content of dataset


Name :
BOTnet_ACAC_2022_train_600K_MD
Authors :
Ilyes Batatia, Simon Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi
Description :
500 decorrelated geometries sampled from 600 K xTB MD run. Acetylacetone dataset generated from a long molecular dynamics simulation at 300 K using a Langevin thermostat at the semi-empirical GFN2-xTB level of theory. Configurations were sampled at an interval of 1 ps and the resulting set of configurations were recomputed with density functional theory using the PBE exchange-correlation functional with D3 dispersion correction and def2-SVP basis set and VeryTightSCF convergence settings using the ORCA electronic structure package.
Cite As :
Batatia, I., Batzner, S., Kovács, D. P., Musaelian, A., Simm, G. N. C., Drautz, R., Ortner, C., Kozinsky, B., and Csányi, G. "BOTnet ACAC 2022 train 600K MD." ColabFit, 2023. https://doi.org/10.60732/7239a192.
ColabFit ID :
Date Added :
2023-07-14
License :
MIT
Downloads :
25
Num. Configurations :
500
Num. Atoms :
7,500
Calculated Property Types :
atomic_forces energy
Elements :
C (33.33%) H (53.33%) O (13.33%)
Methods :
DFT-PBE+D3
Software :
ORCA 5.0
Spec File :
Configuration Sets by Name :
Configuration Sets by ID :
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