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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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pbc
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software
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method
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adsorption_energy
float64
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_nconfigurations
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dataset_cauchy_stress_count
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dataset_electronic_band_gap_count
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dataset_energy_variance
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dataset_formation_energy_count
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dataset_last_modified
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dataset_dimension_types
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C12H12N2O
C12H12N2O
A12B12C2D
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MD_1086845055867124744315202
2024-08-16T14:54:51
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MD_6829391452746235586557108
null
[ "test_300K_1428" ]
[ "DS_i4hwummq4c7j_0" ]
2023-12-01T23:03:11
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3BPA_test_300K
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with MD simulations performed at 300K from 3BPA, 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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3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
C12H12N2O
C12H12N2O
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MD_1086845055867124744315202
2024-08-16T14:22:34
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MD_2932724450300883187076889
null
[ "test_300K_727" ]
[ "DS_i4hwummq4c7j_0" ]
2023-12-01T23:03:11
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3BPA_test_300K
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with MD simulations performed at 300K from 3BPA, 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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10.60732/5737de70
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DS_i4hwummq4c7j_0
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
C12H12N2O
C12H12N2O
A12B12C2D
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MD_1086845055867124744315202
2024-08-16T14:40:13
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MD_8140569289740034849566818
null
[ "test_300K_29" ]
[ "DS_i4hwummq4c7j_0" ]
2023-12-01T23:03:11
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3BPA_test_300K
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with MD simulations performed at 300K from 3BPA, 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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10.60732/5737de70
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DS_i4hwummq4c7j_0
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
C12H12N2O
C12H12N2O
A12B12C2D
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Test configurations with MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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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3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_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 MD simulations performed at 300K from 3BPA, 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_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_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 MD simulations performed at 300K from 3BPA, 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_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_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 MD simulations performed at 300K from 3BPA, 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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DS_i4hwummq4c7j_0
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C12H12N2O
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3BPA_test_300K
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with MD simulations performed at 300K from 3BPA, 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_i4hwummq4c7j_0
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
C12H12N2O
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3BPA_test_300K
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with MD simulations performed at 300K from 3BPA, 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_i4hwummq4c7j_0
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
C12H12N2O
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3BPA_test_300K
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with MD simulations performed at 300K from 3BPA, 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_i4hwummq4c7j_0
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
C12H12N2O
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Test configurations with MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_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 MD simulations performed at 300K from 3BPA, 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_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_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 MD simulations performed at 300K from 3BPA, 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_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
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Test configurations with MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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 MD simulations performed at 300K from 3BPA, 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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MD_1086845055867124744315202
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MD_9174208413220235349194748
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[ "test_300K_103" ]
[ "DS_i4hwummq4c7j_0" ]
2023-12-01T23:03:11
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3BPA_test_300K
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with MD simulations performed at 300K from 3BPA, 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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{'source-publication': 'https://doi.org/10.1021/acs.jctc.1c00647', 'source-data': 'https://doi.org/10.1021/acs.jctc.1c00647', 'other': None}
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DS_i4hwummq4c7j_0
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
C12H12N2O
C12H12N2O
A12B12C2D
[ 6, 6, 6, 1, 6, 8, 7, 7, 1, 1, 6, 1, 1, 6, 6, 1, 1, 6, 6, 6, 1, 6, 1, 6, 1, 1, 1 ]
[ "C", "H", "N", "O" ]
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DFT-ωB97X
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MD_1086845055867124744315202
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MD_6444760675081517970878426
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[ "test_300K_933" ]
[ "DS_i4hwummq4c7j_0" ]
2023-12-01T23:03:11
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CO_1090508788542533021992857
3BPA_test_300K
[ "Dávid Péter Kovács", "Cas van der Oord", "Jiri Kucera", "Alice E. A. Allen", "Daniel J. Cole", "Christoph Ortner", "Gábor Csányi" ]
Test configurations with MD simulations performed at 300K from 3BPA, 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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1,669
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2023-12-01T18:03:29
[ [ 1, 1, 1 ] ]
[ 3 ]
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[ 0.4444444444444444, 0.4444444444444444, 0.07407407407407407, 0.037037037037037035 ]
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}
10.60732/5737de70
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DS_i4hwummq4c7j_0
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
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Dataset

3BPA test 300K

Description

Test configurations with MD simulations performed at 300K from 3BPA, 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

1669

Number of atoms

45063

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 300K. ColabFit, 2023. https://doi.org/10.60732/5737de70

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