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chemical_formula_hill
string
chemical_formula_reduced
string
chemical_formula_anonymous
string
atomic_numbers
sequence
elements
sequence
elements_ratios
sequence
nelements
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software
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method
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adsorption_energy
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atomic_forces
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atomization_energy
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cauchy_stress
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cauchy_stress_volume_normalized
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electronic_band_gap
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electronic_band_gap_type
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energy
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formation_energy
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max_force_norm
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mean_force_norm
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property_object_metadata
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property_object_last_modified
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dataset_nproperty_objects
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dataset_nconfigurations
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dataset_cauchy_stress_count
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dataset_electronic_band_gap_count
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dataset_energy_mean
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dataset_energy_variance
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dataset_formation_energy_count
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dataset_last_modified
timestamp[ns]
dataset_dimension_types
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C12H12N2O
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2024-08-16T15:11:30
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[ "test_dih_beta180_694" ]
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2023-12-01T23:04:45
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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2024-08-16T14:21:06
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[ "test_dih_beta180_502" ]
[ "DS_ilijykl0t0fn_0" ]
2023-12-01T23:04:45
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3BPA_test_dih_beta180
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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3BPA_test_dih_beta180__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_ilijykl0t0fn_0
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2024-08-16T14:15:31
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2023-12-01T23:04:45
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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DS_ilijykl0t0fn_0
3BPA_test_dih_beta180__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_ilijykl0t0fn_0
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "test_dih_beta180_928" ]
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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3BPA_test_dih_beta180
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[ "test_dih_beta180_1439" ]
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2023-12-01T23:04:45
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3BPA_test_dih_beta180
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
[ "C", "H", "N", "O" ]
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CC-BY-4.0
{'source-publication': 'https://doi.org/10.1021/acs.jctc.1c00647', 'source-data': 'https://doi.org/10.1021/acs.jctc.1c00647', 'other': None}
10.60732/e9fb7e4a
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DS_ilijykl0t0fn_0
3BPA_test_dih_beta180__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_ilijykl0t0fn_0
C12H12N2O
C12H12N2O
A12B12C2D
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MD_1086845055867124744315202
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MD_1051697899229052159941954
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[ "test_dih_beta180_1184" ]
[ "DS_ilijykl0t0fn_0" ]
2023-12-01T23:04:45
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3BPA_test_dih_beta180
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
[ "C", "H", "N", "O" ]
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2,350
63,450
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2,350
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2,350
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2023-12-01T18:04:53
[ [ 1, 1, 1 ] ]
[ 3 ]
2023
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CC-BY-4.0
{'source-publication': 'https://doi.org/10.1021/acs.jctc.1c00647', 'source-data': 'https://doi.org/10.1021/acs.jctc.1c00647', 'other': None}
10.60732/e9fb7e4a
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DS_ilijykl0t0fn_0
3BPA_test_dih_beta180__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_ilijykl0t0fn_0
End of preview. Expand in Data Studio

Dataset

3BPA test dih beta180

Description

Test configurations with fixed value for dihedral beta in alpha-gamma plane of 180 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.

Additional details stored in dataset columns prepended with "dataset_".

Dataset authors

Dávid Péter Kovács, Cas van der Oord, Jiri Kucera, Alice E. A. Allen, Daniel J. Cole, Christoph Ortner, Gábor Csányi

Publication

https://doi.org/10.1021/acs.jctc.1c00647

Original data link

https://doi.org/10.1021/acs.jctc.1c00647

License

CC-BY-4.0

Number of unique molecular configurations

2350

Number of atoms

63450

Elements included

C, H, N, O

Properties included

energy, atomic forces, cauchy stress

Cite this dataset

Kovács, D. P., Oord, C., Kucera, J., Allen, A. E. A., Cole, D. J., Ortner, C., and Csányi, G. 3BPA test dih beta180. ColabFit, 2023. https://doi.org/10.60732/e9fb7e4a

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