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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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[
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3BPA_test_300K
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[
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"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[
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[
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"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
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"N",
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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CO_6191802166056244977745134
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3BPA_test_300K
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"Jiri Kucera",
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"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[
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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 MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
"O"
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DS_i4hwummq4c7j_0
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3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
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C12H12N2O
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[
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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 MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
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MD_1086845055867124744315202
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[
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"Cas van der Oord",
"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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MD_1086845055867124744315202
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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 MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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"N",
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[
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[
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"Cas van der Oord",
"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
"O"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Cas van der Oord",
"Jiri Kucera",
"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
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[
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[
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CO_1479483840447129252773613
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3BPA_test_300K
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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 MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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"N",
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MD_1086845055867124744315202
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[
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[
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CO_6259451228289112953600341
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3BPA_test_300K
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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 MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
"O"
] | 4 | 1,669 | 1,669 | 45,063 | 0 | 1,669 | 0 | 1,669 | 0 | 1,669 | -17,660.421858 | 0.026915 | 0 | 2023-12-01T18:03:29 |
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DS_i4hwummq4c7j_0
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3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
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C12H12N2O
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[
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3BPA_test_300K
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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 MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
"O"
] | 4 | 1,669 | 1,669 | 45,063 | 0 | 1,669 | 0 | 1,669 | 0 | 1,669 | -17,660.421858 | 0.026915 | 0 | 2023-12-01T18:03:29 |
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DS_i4hwummq4c7j_0
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Jiri Kucera",
"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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"N",
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"Cas van der Oord",
"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Jiri Kucera",
"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
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"N",
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Jiri Kucera",
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"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Cas van der Oord",
"Jiri Kucera",
"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
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[
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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 MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
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"N",
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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 MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
"O"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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[
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"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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"N",
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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C12H12N2O
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[
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[
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"Jiri Kucera",
"Alice E. A. Allen",
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"Christoph Ortner",
"Gábor Csányi"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
"O"
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
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Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
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[] | null | null | null | -17,660.490433 | null | 1.409592 | 3.589342 |
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MD_1086845055867124744315202
| 2024-08-16T15:14:37 |
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MD_9287553627722174969465029
| null |
[
"test_300K_1634"
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[
"DS_i4hwummq4c7j_0"
] | 2023-12-01T23:03:11 |
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CO_8695200200798198314836346
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3BPA_test_300K
|
[
"Dávid Péter Kovács",
"Cas van der Oord",
"Jiri Kucera",
"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
"O"
] | 4 | 1,669 | 1,669 | 45,063 | 0 | 1,669 | 0 | 1,669 | 0 | 1,669 | -17,660.421858 | 0.026915 | 0 | 2023-12-01T18:03:29 |
[
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CC-BY-4.0
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{'source-publication': 'https://doi.org/10.1021/acs.jctc.1c00647', 'source-data': 'https://doi.org/10.1021/acs.jctc.1c00647', 'other': None}
|
10.60732/5737de70
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DS_i4hwummq4c7j_0
|
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
|
C12H12N2O
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C12H12N2O
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A12B12C2D
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DFT-ωB97X
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[] | null | null | null | -17,660.510729 | null | 1.183225 | 3.709263 |
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|
MD_1086845055867124744315202
| 2024-08-16T15:07:11 |
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PO_9316287013505203398853983
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|
MD_1189112610583599008658979
| null |
[
"test_300K_220"
] |
[
"DS_i4hwummq4c7j_0"
] | 2023-12-01T23:03:11 |
7084114407621406344571712739470954356375619777521762706656831566348544065507838800699732850699702565096089562181222261923594328992285015105318148563316638
|
CO_7084114407621406344571712
|
3BPA_test_300K
|
[
"Dávid Péter Kovács",
"Cas van der Oord",
"Jiri Kucera",
"Alice E. A. Allen",
"Daniel J. Cole",
"Christoph Ortner",
"Gábor Csányi"
] |
Test configurations with MD simulations performed at 300K from 3BPA, used to showcase the performance of linear atomic cluster expansion (ACE) force fields in a machine learning model to predict the potential energy surfaces of organic molecules.
|
[
"C",
"H",
"N",
"O"
] | 4 | 1,669 | 1,669 | 45,063 | 0 | 1,669 | 0 | 1,669 | 0 | 1,669 | -17,660.421858 | 0.026915 | 0 | 2023-12-01T18:03:29 |
[
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[
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2023
|
[
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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}
|
10.60732/5737de70
|
858961823238077671629249081432826806390543202282938943667175074929273618501088355783510765591272880179637709954111929697548615310032839261296799325172367
|
DS_i4hwummq4c7j_0
|
3BPA_test_300K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_i4hwummq4c7j_0
|
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