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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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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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[ "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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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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[ "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__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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[ "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 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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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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C12H12N2O
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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__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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[ "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__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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[ "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__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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3BPA_test_dih_beta180__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_ilijykl0t0fn_0
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[ "test_dih_beta180_451" ]
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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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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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[ "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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{"dihedrals": [87.0, 180.0, 221.0], "hash": "12934986095536689633610056685390468376566151267235632178327552859027021229680055698007552641759495221295721846213771996665581657831622307294333328707077233", "id": "MD_1293498609553668963361005"}
MD_1293498609553668963361005
null
[ "test_dih_beta180_436" ]
[ "DS_ilijykl0t0fn_0" ]
2023-12-01T23:04:45
7442942345791469661692451203336995848521472919062603355278586781298671397389971095576531014331034951501679785734206316892938947705225248222030770068469042
CO_7442942345791469661692451
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" ]
4
2,350
2,350
63,450
0
2,350
0
2,350
0
2,350
-17,661.206233
0.018122
0
2023-12-01T18:04:53
[ [ 1, 1, 1 ] ]
[ 3 ]
2023
[ 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/e9fb7e4a
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DS_ilijykl0t0fn_0
3BPA_test_dih_beta180__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_ilijykl0t0fn_0