BOTnet -- ColabFit
Collection
Datasets from BOTnet in ColabFit format
•
7 items
•
Updated
property_id
string | property_hash
string | last_modified
timestamp[us] | dataset_id
string | multiplicity
int32 | software
string | method
string | energy
float64 | atomic_forces
list | cauchy_stress
list | cauchy_stress_volume_normalized
bool | electronic_band_gap
float64 | electronic_band_gap_type
string | formation_energy
float64 | adsorption_energy
float64 | atomization_energy
float64 | max_force_norm
float64 | mean_force_norm
float64 | energy_above_hull
float64 | configuration_id
string | configuration_hash
string | structure_hash
string | cell
list | positions
list | pbc
list | chemical_formula_hill
string | chemical_formula_reduced
string | chemical_formula_anonymous
string | elements
list | elements_ratios
list | atomic_numbers
list | nsites
int32 | nelements
int32 | nperiodic_dimensions
int32 | dimension_types
list | names
list | labels
list | property_metadata_path
string | configuration_metadata_path
string | hash
string | configuration_metadata
string | property_metadata
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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End of preview. Expand
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Cite this dataset
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
Cite this dataset
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/10.60732/7239a192This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_632yputkfhpg_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
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Dataset Name
BOTnet ACAC 2022 train 600K MD
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.
Dataset authors
Ilyes Batatia, Simon Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi
Publication
https://doi.org/10.1038/s42256-024-00956-x
Original data link
https://github.com/davkovacs/BOTNet-datasets
License
MIT
Number of unique molecular configurations
500
Number of atoms
7500
Elements included
C, H, O
Properties included
energy, atomic forces
Usage
ds.parquet: Aggregated dataset information.co/directory: Configuration rows each include a structure, calculated properties, and metadata.cs/directory : Configuration sets are subsets of configurations grouped by some common characteristic. Ifcs/does not exist, no configurations sets have been defined for this dataset.cs_co_map/directory : The mapping of configurations to configuration sets (if defined).
ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:
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Number of rows:
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