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"Daniel J. Cole",
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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_199ama4h9t7m_0
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C12H12N2O
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3BPA_test_dih_beta150
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[
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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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10.60732/1c4b1e1c
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DS_199ama4h9t7m_0
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3BPA_test_dih_beta150__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_199ama4h9t7m_0
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C12H12N2O
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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[
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[
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"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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",
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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",
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"O"
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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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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[
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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 150 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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[
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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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[
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"Cas van der Oord",
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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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[
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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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",
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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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[
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"N",
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[
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"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 150 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_beta150
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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 150 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 | -17,661.153854 | 0.009458 | 0 | 2023-12-01T18:04:44 |
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DS_199ama4h9t7m_0
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3BPA_test_dih_beta150
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[
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"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 150 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 | -17,661.153854 | 0.009458 | 0 | 2023-12-01T18:04:44 |
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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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"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Daniel J. Cole",
"Christoph Ortner",
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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[
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[
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"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 150 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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"N",
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DS_199ama4h9t7m_0
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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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[
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"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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[
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[
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"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 150 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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"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 150 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",
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DS_199ama4h9t7m_0
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[
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"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 150 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",
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"N",
"O"
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DS_199ama4h9t7m_0
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Cas van der Oord",
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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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"Cas van der Oord",
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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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[
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[
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"Cas van der Oord",
"Jiri Kucera",
"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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",
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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[
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[
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"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 150 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 | -17,661.153854 | 0.009458 | 0 | 2023-12-01T18:04:44 |
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10.60732/1c4b1e1c
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DS_199ama4h9t7m_0
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3BPA_test_dih_beta150__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_199ama4h9t7m_0
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C12H12N2O
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[
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3BPA_test_dih_beta150
|
[
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"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 150 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 | -17,661.153854 | 0.009458 | 0 | 2023-12-01T18:04:44 |
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10.60732/1c4b1e1c
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DS_199ama4h9t7m_0
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3BPA_test_dih_beta150__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_199ama4h9t7m_0
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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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"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 150 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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[
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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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[
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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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[
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"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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 150 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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"Gábor Csányi"
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Test configurations with fixed value for dihedral beta in alpha-gamma plane of 150 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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"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
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{"dihedrals": [179.0, 150.0, 95.0], "hash": "12691852093038626297207978376553186112187198337840329256013076484464605528102112596430805680180938035540206041265101120131247692616762270579205246388309042", "id": "MD_1269185209303862629720797"}
|
MD_1269185209303862629720797
| null |
[
"test_dih_beta150_1565"
] |
[
"DS_199ama4h9t7m_0"
] | 2023-12-01T23:04:35 |
7492427616608150135540259288575263282579895751178795244444619678048855211999693054045358790181656885428305754500461161637626904052436291713375129307462136
|
CO_7492427616608150135540259
|
3BPA_test_dih_beta150
|
[
"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 150 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 | -17,661.153854 | 0.009458 | 0 | 2023-12-01T18:04:44 |
[
[
1,
1,
1
]
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[
3
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2023
|
[
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0.037037037037037035
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CC-BY-4.0
|
{'source-publication': 'https://doi.org/10.1021/acs.jctc.1c00647', 'source-data': 'https://doi.org/10.1021/acs.jctc.1c00647', 'other': None}
|
10.60732/1c4b1e1c
|
10718612364202825117041962661964423644437445498120906886876715119377249881186529099659497513553212911936889111374804277351108862253992855586807653770199316
|
DS_199ama4h9t7m_0
|
3BPA_test_dih_beta150__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_199ama4h9t7m_0
|
C12H12N2O
|
C12H12N2O
|
A12B12C2D
|
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[
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true,
true,
true
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ORCA
|
DFT-ωB97X
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] | null |
[] | null | null | null | -17,661.198753 | null | 0.288334 | 2.728698 |
{"hash": "10868450558671247443152026947160338505683745266658651051718065983487878962987857602829315249215796444208488632888003673539585986066311769564391053988452926", "id": "MD_1086845055867124744315202"}
|
MD_1086845055867124744315202
| 2024-08-16T14:54:46 |
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|
PO_1330405197470004743328274
|
{"dihedrals": [119.0, 150.0, 137.0], "hash": "11975444873023699112085803127487560012423802571400816879465261682525462543025416201384978214863631547211847735448257813861112055143261352176718563435033846", "id": "MD_1197544487302369911208580"}
|
MD_1197544487302369911208580
| null |
[
"test_dih_beta150_822"
] |
[
"DS_199ama4h9t7m_0"
] | 2023-12-01T23:04:35 |
11364655793408446525285974961126148238751585427925521269124547266475387611943828520816230630285419867111631240386753762274140313941458545867106980610209148
|
CO_1136465579340844652528597
|
3BPA_test_dih_beta150
|
[
"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 150 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 | -17,661.153854 | 0.009458 | 0 | 2023-12-01T18:04:44 |
[
[
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}
|
10.60732/1c4b1e1c
|
10718612364202825117041962661964423644437445498120906886876715119377249881186529099659497513553212911936889111374804277351108862253992855586807653770199316
|
DS_199ama4h9t7m_0
|
3BPA_test_dih_beta150__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_199ama4h9t7m_0
|
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