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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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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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[ "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
C12H12N2O
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[ "test_dih_beta180_395" ]
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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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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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[ "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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[ "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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[ "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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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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[ "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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[ "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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[ "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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[ "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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{"dihedrals": [107.0, 180.0, 167.0], "hash": "1097397310206789222216303690980044326346170580798306261506254963959042561774869066400093181135022207057871993933627643330005762470728779498959457435228507", "id": "MD_1097397310206789222216303"}
MD_1097397310206789222216303
null
[ "test_dih_beta180_677" ]
[ "DS_ilijykl0t0fn_0" ]
2023-12-01T23:04:45
6010520751494731663590390993462120619654238236026193818017381591836683497284925703521589572712157078039902962007413307190001156474086051294511375366631205
CO_6010520751494731663590390
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
9367248763475021850697653457915360094447517972612737450172450376144145127416950844107156499621219514145413449591340727144456677821679114667242837945337653
DS_ilijykl0t0fn_0
3BPA_test_dih_beta180__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_ilijykl0t0fn_0