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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 degreesfrom 3BPA dataset. Used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
[ "C", "H", "N", "O" ]
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[ "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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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 120 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_beta120_870" ]
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3BPA_test_dih_beta120
[ "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 120 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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[ [ 0.00051555, 0.00192686, 0.00075979 ], [ -1.12891627, -0.12053534, -0.9980402 ], [ -0.00040917, 0.00105225, 0.0022768 ], [ -0.00286317, -0.00019841, -0.00353082 ], [ -0.01747783, 0.0469132, 0.190631 ], [ 1.89502545, 1.88721114, 1.37174255 ], [ -0.01412752, 0.05057032, -0.10908986 ], [ -0.00232881, 0.00182068, -0.0011686 ], [ 0.1101937, 0.02102717, -0.01025931 ], [ 0.00002663, -0.00382281, -0.00146309 ], [ -0.00374108, 0.0017732, -0.00237132 ], [ -0.00722657, 0.00302756, -0.00238413 ], [ -0.00273493, -0.00025653, 0.00263478 ], [ -1.38031821, -1.33795722, -0.23475169 ], [ 0.83675768, -0.47769492, -0.24558902 ], [ 0.00072969, 0.00049126, -0.00177856 ], [ 0.00178294, 0.00069703, -0.00165318 ], [ -0.00150108, 0.00199336, 0.00048365 ], [ -0.26989623, -0.08696689, 0.03843628 ], [ -0.0024871, 0.00181476, 0.0016693 ], [ 0.00005198, 0.00095942, 0.00084788 ], [ -0.00374873, 0.00140128, 0.00075168 ], [ -0.00140663, 0.00438728, 0.00032241 ], [ -0.00098374, -0.00024275, 0.00100663 ], [ -0.00158738, 0.00092188, 0.00270972 ], [ -0.00129313, 0.00078625, -0.00026662 ], [ -0.00203603, -0.00110001, -0.00192608 ] ]
null
[]
null
null
null
-17,661.136502
null
0.304753
3.005722
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MD_1086845055867124744315202
2024-08-16T14:21:19
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PO_1024470374325563987741165
{"dihedrals": [123.0, 120.0, 251.0], "hash": "6242609947209642306921483334963025830091036176685412879771531255126641405861567004097967933113841314355118260814102883683574427167235920864756588311670610", "id": "MD_6242609947209642306921483"}
MD_6242609947209642306921483
null
[ "test_dih_beta120_891" ]
[ "DS_8cg3pdvxt0pa_0" ]
2023-12-01T23:04:24
606081117875452160843003302196795686022296676931924630589306984223460655092593847017836063010498146541273563245759505764232744241569607360549950189257836
CO_6060811178754521608430033
3BPA_test_dih_beta120
[ "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 120 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
2,347
2,347
63,369
0
2,347
0
2,347
0
2,347
-17,661.110219
0.003184
0
2023-12-01T18:04:34
[ [ 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}
10.60732/09d00e4e
10185573093864123849716176184559073216212497469109140478569682756756964644641629331520778206484859340812213383948133111023213290861443756269526451083246522
DS_8cg3pdvxt0pa_0
3BPA_test_dih_beta120__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_8cg3pdvxt0pa_0