CA-9 -- ColabFit
Collection
Datasets from CA-9 in ColabFit format
•
9 items
•
Updated
Datasets:
Dataset Viewer
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PO_1000994101746605863908054
|
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| 2025-04-16T19:57:47
|
DS_l7inbtql4ea9_0
| 1
|
VASP
|
DFT-PBE
| -397.81036
|
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] | null | null | null | null | null | null | 5.93448
| 2.49356
| null |
CO_1419955931187398702199692
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C50
|
C
|
A
|
[
"C"
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[
1
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| 1
| 3
|
[
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1
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[
"BR_validation__1724",
"BB_training__15191",
"CA-9_training__18790"
] | null |
data/MD/4357/MD_1024398629573454165794357.json
| null | null | null |
{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
|
PO_1000907018977108370906599
|
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| 2025-04-17T18:37:27
|
DS_l7inbtql4ea9_0
| 1
|
VASP
|
DFT-PBE
| -365.166531
|
[
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DS_l7inbtql4ea9_0
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DS_l7inbtql4ea9_0
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VASP
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DS_l7inbtql4ea9_0
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| 2025-04-16T20:28:56
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DS_l7inbtql4ea9_0
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VASP
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DFT-PBE
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DS_l7inbtql4ea9_0
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DS_l7inbtql4ea9_0
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C59
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C
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DS_l7inbtql4ea9_0
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C50
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C
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A
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| 2025-04-16T16:49:26
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DS_l7inbtql4ea9_0
| 1
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VASP
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DFT-PBE
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DS_l7inbtql4ea9_0
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DS_l7inbtql4ea9_0
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VASP
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DS_l7inbtql4ea9_0
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C59
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DS_l7inbtql4ea9_0
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VASP
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DS_l7inbtql4ea9_0
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DS_l7inbtql4ea9_0
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VASP
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| 2025-04-16T16:10:44
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DS_l7inbtql4ea9_0
| 1
|
VASP
|
DFT-PBE
| -521.924345
|
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| 3.114596
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CO_1232339743286869096696306
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true,
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C60
|
C
|
A
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[
"C"
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1
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[
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data/MD/4357/MD_1024398629573454165794357.json
| null | null | null |
{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
|
PO_1000470591897298929270085
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| 2025-04-16T16:06:08
|
DS_l7inbtql4ea9_0
| 1
|
VASP
|
DFT-PBE
| -389.78189
|
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DS_l7inbtql4ea9_0
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| 2025-04-16T16:03:20
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DS_l7inbtql4ea9_0
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VASP
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DFT-PBE
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DS_l7inbtql4ea9_0
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DS_l7inbtql4ea9_0
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DS_l7inbtql4ea9_0
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DS_l7inbtql4ea9_0
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End of preview. Expand
in Data Studio
Cite this dataset
Hedman, D., Rothe, T., Johansson, G., Sandin, F., Larsson, J. A., and Miyamoto, Y. CA-9 BB training. ColabFit, 2023. https://doi.org/10.60732/f3bbbd36
Cite this dataset
Hedman, D., Rothe, T., Johansson, G., Sandin, F., Larsson, J. A., and Miyamoto, Y. CA-9 BB training. ColabFit, 2023. https://doi.org/10.60732/f3bbbd36This 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_l7inbtql4ea9_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
https://materials.colabfit.org
Dataset Name
CA-9 BB training
Description
Binning-binning configurations from CA-9 dataset used for training NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
Dataset authors
Daniel Hedman, Tom Rothe, Gustav Johansson, Fredrik Sandin, J. Andreas Larsson, Yoshiyuki Miyamoto
Publication
https://doi.org/10.1016/j.cartre.2021.100027
Original data link
https://doi.org/10.24435/materialscloud:6h-yj
License
CC-BY-4.0
Number of unique molecular configurations
20006
Number of atoms
1053753
Elements included
C
Properties included
energy, atomic forces, cauchy stress
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:
- Downloads last month
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Size of downloaded dataset files:
54.8 MB
Size of the auto-converted Parquet files:
54.8 MB
Number of rows:
20,007