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| Test configurations with MD simulations performed at 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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 1200K 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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| 2023-12-01T23:03:55 | 8578937420317771373408333832779506803012982771066436591883754125562435682570409120467585257449891585614462868259665418387911318098572056800051285602915201 | CO_8578937420317771373408333 | 3BPA_test_1200K | [
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| Test configurations with MD simulations performed at 1200K 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 1200K 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 1200K 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 1200K 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 | null | -17,657.832843 | null | 2.809294 | 6.651481 | {"hash": "10868450558671247443152026947160338505683745266658651051718065983487878962987857602829315249215796444208488632888003673539585986066311769564391053988452926", "id": "MD_1086845055867124744315202"} | MD_1086845055867124744315202 | 2024-08-16T15:21:26 | 3447999094881637510591539576448363725411345474456329973674822182969068943182425203360536858387223320578452894295975427757160981999397773058518902573364386 | PO_3447999094881637510591539 | {"dihedrals": [150.13, 301.18, 287.51], "hash": "8779866879042696939937962725925870729742784469650082633878587138929069698139803328594674373955464616838391533364955934105349880649922398961436235266972461", "id": "MD_8779866879042696939937962"} | MD_8779866879042696939937962 | null | [
"test_1200K_1122"
]
| [
"DS_xaasqmrdv28s_0"
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| 2023-12-01T23:03:55 | 11174392356261052262919482248530637261881679574101695536076741658206110266190518077440888416165768677407973164296398742048875446328386412576086069397459170 | CO_1117439235626105226291948 | 3BPA_test_1200K | [
"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 1200K 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 | 2,139 | 2,139 | 57,753 | 0 | 2,139 | 0 | 2,139 | 0 | 2,139 | -17,657.384151 | 0.43537 | 0 | 2023-12-01T18:04:16 | [
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C12H12N2O | C12H12N2O | A12B12C2D | [
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| null | []
| null | null | null | -17,656.918978 | null | 3.001148 | 7.795287 | {"hash": "10868450558671247443152026947160338505683745266658651051718065983487878962987857602829315249215796444208488632888003673539585986066311769564391053988452926", "id": "MD_1086845055867124744315202"} | MD_1086845055867124744315202 | 2024-08-16T14:50:29 | 6715940896826982856027761462535681431592221065433467607270348433560197075589457110622052987674460868859744297853358377095067515958261942602239341113799865 | PO_6715940896826982856027761 | {"dihedrals": [258.15, 197.06, 145.9], "hash": "1049376091247820967441880680993881046169202997297827794518247513307636804417897609244126174426724533978031937845494947332303923236682145722290918413253947", "id": "MD_1049376091247820967441880"} | MD_1049376091247820967441880 | null | [
"test_1200K_393"
]
| [
"DS_xaasqmrdv28s_0"
]
| 2023-12-01T23:03:55 | 1157623713701209879064056230545486464093809010682697561465835548688399707856179474777596804425964473880577954587686530447899781340061900725380233249082571 | CO_1157623713701209879064056 | 3BPA_test_1200K | [
"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 1200K 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 | 2,139 | 2,139 | 57,753 | 0 | 2,139 | 0 | 2,139 | 0 | 2,139 | -17,657.384151 | 0.43537 | 0 | 2023-12-01T18:04:16 | [
[
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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} | 10.60732/397ba16b | 7899875445740390853525518874950735106564511781852407552402574170731136271469827544313302924695625801383632045682941220070723492003297862187522002740424720 | DS_xaasqmrdv28s_0 | 3BPA_test_1200K__Kovács-Oord-Kucera-Allen-Cole-Ortner-Csányi__DS_xaasqmrdv28s_0 |
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