ANI-Al -- ColabFit
Collection
Datasets from ANI-Al in ColabFit format
•
2 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PO_1001077660686322996544987
|
10010776606863229965449879659844005351707534903347485372980931586082777695802794984085152265933561859528245130267699141454832594187077802176801693300721353
| 2025-04-16T17:25:18
|
DS_tz8gsj3xi2g4_0
| 1
|
Quantum ESPRESSO
|
DFT-PBE
| -390.326853
|
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DS_tz8gsj3xi2g4_0
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data/MD/5914/MD_6643939057733462811145914.json
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data/MD/7850/MD_1171222972199863025397850.json
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{"fermi": 0.16446414228999998, "hash": "11712229721998630253978504622708666089147193342267253497635791557448028763320377040990441380882894073302824746222981096831567656387040788915940527117595211", "id": "MD_1171222972199863025397850"}
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PO_1001486639067864880701084
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DS_tz8gsj3xi2g4_0
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Quantum ESPRESSO
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DFT-PBE
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DS_tz8gsj3xi2g4_0
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data/MD/5914/MD_6643939057733462811145914.json
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data/MD/1541/MD_6360332921991469246741541.json
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{"fermi": 0.16134412671999998, "hash": "6360332921991469246741541852143209955649084063004683363495322604314862147952738562554727586007945158513518098194049715584990084855441519503916878052974964", "id": "MD_6360332921991469246741541"}
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PO_1000290114613946657722146
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| 2025-04-16T20:09:21
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DS_tz8gsj3xi2g4_0
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Quantum ESPRESSO
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DFT-PBE
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data/MD/5914/MD_6643939057733462811145914.json
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data/MD/0505/MD_1912161186259246042960505.json
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{"fermi": 0.14542432996, "hash": "1912161186259246042960505452713624532655018964366920362994548218700028232095514858925670624127061576003341362167743187229740485550393545599333010088576215", "id": "MD_1912161186259246042960505"}
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{"input": {"kpoints": "3x3x3"}, "hash": "6643939057733462811145914405395890628028266156972818050701550021368872136636671133015855377434037458505168737175762776701855531341958525963369589997719194", "id": "MD_6643939057733462811145914"}
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PO_1000678680341864481116974
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| 2025-04-16T15:45:01
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DS_tz8gsj3xi2g4_0
| 1
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Quantum ESPRESSO
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DFT-PBE
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data/MD/5914/MD_6643939057733462811145914.json
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data/MD/7742/MD_9698786206820913047487742.json
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{"fermi": 0.28809613735, "hash": "9698786206820913047487742890159813627934586748998429852579634750617106233359410334339289171022535277472880902145276774255906209015821683760546549399807711", "id": "MD_9698786206820913047487742"}
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PO_1000698294153809273691798
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| 2025-04-16T18:10:42
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DS_tz8gsj3xi2g4_0
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Quantum ESPRESSO
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DFT-PBE
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PO_1000657581078236094986721
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DS_tz8gsj3xi2g4_0
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Quantum ESPRESSO
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DFT-PBE
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PO_4924420130120905810598141
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| 2025-04-16T16:07:46
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DS_tz8gsj3xi2g4_0
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Quantum ESPRESSO
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DFT-PBE
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| 2025-04-16T17:57:37
|
DS_tz8gsj3xi2g4_0
| 1
|
Quantum ESPRESSO
|
DFT-PBE
| -209.7739
|
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data/MD/5624/MD_6923955494976481858385624.json
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PO_4925902133272263333453907
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| 2025-04-16T16:32:22
|
DS_tz8gsj3xi2g4_0
| 1
|
Quantum ESPRESSO
|
DFT-PBE
| -338.080946
|
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data/MD/5914/MD_6643939057733462811145914.json
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data/MD/8327/MD_8724948331634050238028327.json
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{"fermi": 0.20898959417, "hash": "8724948331634050238028327583931579342307990370831316829204929506353004003225958927912010908998129423892647769986573586162749075916323845167068382388246295", "id": "MD_8724948331634050238028327"}
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|
End of preview. Expand
in Data Studio
Cite this dataset
Smith, J. S., Nebgen, B., Mathew, N., Chen, J., Lubbers, N., Burakovsky, L., Tretiak, S., Nam, H. A., Germann, T., Fensin, S., and Barros, K. ANI-Al NC2021-train. ColabFit, 2023. https://doi.org/10.60732/af254882
Cite this dataset
Smith, J. S., Nebgen, B., Mathew, N., Chen, J., Lubbers, N., Burakovsky, L., Tretiak, S., Nam, H. A., Germann, T., Fensin, S., and Barros, K. ANI-Al NC2021-train. ColabFit, 2023. https://doi.org/10.60732/af254882This 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_tz8gsj3xi2g4_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
https://materials.colabfit.org
Dataset Name
ANI-Al NC2021-train
Description
Approximately 2800 configurations from a train dataset–one of a pair of train/test datasets of aluminum in crystal and melt phases, used for training and testing an ANI neural network model.
Dataset authors
Justin S. Smith, Benjamin Nebgen, Nithin Mathew, Jie Chen, Nicholas Lubbers, Leonid Burakovsky, Sergei Tretiak, Hai Ah Nam, Timothy Germann, Saryu Fensin, Kipton Barros
Publication
https://doi.org/10.1038/s41467-021-21376-0
Original data link
https://github.com/atomistic-ml/ani-al
License
CC-BY-4.0
Number of unique molecular configurations
2779
Number of atoms
363129
Elements included
Al
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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Size of downloaded dataset files:
18.2 MB
Size of the auto-converted Parquet files:
18.2 MB
Number of rows:
2,781