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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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"H",
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| 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 | [
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| null | null | null | -17,661.112629 | null | 0.298099 | 3.141435 | {"hash": "10868450558671247443152026947160338505683745266658651051718065983487878962987857602829315249215796444208488632888003673539585986066311769564391053988452926", "id": "MD_1086845055867124744315202"} | MD_1086845055867124744315202 | 2024-08-16T14:25:35 | 11440924357175772019521163390850846081015556948293229015848776988355242581758133813958222024312793846645993853164168160631689125995211474759529467231295694 | PO_1144092435717577201952116 | {"dihedrals": [199.0, 120.0, 47.0], "hash": "11287414751809932513044607937035009107192216636855064938278032438149221908059164807264646481697338605797851444198837272556406815464259132086441356564505946", "id": "MD_1128741475180993251304460"} | MD_1128741475180993251304460 | null | [
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| [
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| 2023-12-01T23:04:25 | 5076692699024883085770387197012315102498984568696222565281833709822570943195573074976030359015385436835525021703263701293770628086071890887965299778492011 | CO_5076692699024883085770387 | 3BPA_test_dih_beta120 | [
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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 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 | [
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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} | 10.60732/09d00e4e | 10185573093864123849716176184559073216212497469109140478569682756756964644641629331520778206484859340812213383948133111023213290861443756269526451083246522 | DS_8cg3pdvxt0pa_0 | 3BPA_test_dih_beta120__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_8cg3pdvxt0pa_0 |
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