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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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CA-9_BB_validation
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[
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"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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2023
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CC-BY-4.0
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{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
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10.60732/95c19122
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DFT-PBE
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{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
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MD_1024398629573454165794357
| 2024-08-16T14:57:17 |
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PO_1087444914315044394411244
| null | null | null |
[
"BR_training__2756",
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[
"DS_fw7m5d8b0fa9_0",
"DS_tag5zubl21w8_0",
"DS_9cdtww9pcjqd_0",
"DS_8zft35i5sbgd_0"
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CO_5386946635933498700440222
|
CA-9_BB_validation
|
[
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"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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"Yoshiyuki Miyamoto"
] |
Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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CO_5640006324068047199068731
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CA-9_BB_validation
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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2023
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CC-BY-4.0
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{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
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10.60732/95c19122
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
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MD_1024398629573454165794357
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|
[
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"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
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] | 1 | 4,003 | 4,003 | 233,034 | 0 | 4,003 | 0 | 4,003 | 0 | 4,003 | -501.735936 | 10,202.734006 | 0 | 2023-12-01T18:52:50 |
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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2023
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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C50
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
| 2024-08-16T14:33:47 |
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PO_1085014000117723422784405
| null | null | null |
[
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[
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"DS_9cdtww9pcjqd_0",
"DS_mr2qaiqh2sx2_0",
"DS_8zft35i5sbgd_0"
] | 2023-12-01T23:56:36 |
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CO_6912946308309812162493798
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CA-9_BB_validation
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[
"Daniel Hedman",
"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
"C"
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[
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[
3
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2023
|
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1
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CC-BY-4.0
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{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
|
10.60732/95c19122
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DS_8zft35i5sbgd_0
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CA-9_BB_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_8zft35i5sbgd_0
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C72
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C
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{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
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MD_1024398629573454165794357
| 2024-08-16T14:42:16 |
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PO_1600047281125025750553492
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[
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
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{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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CO_7242944628247600112310673
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CA-9_BB_validation
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[
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"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
"C"
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
| 2024-08-16T14:26:43 |
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PO_9823173214183345254257101
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[
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[
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"DS_9cdtww9pcjqd_0",
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
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[
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2023
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{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
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10.60732/95c19122
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C50
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C
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
| 2024-08-16T15:35:20 |
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| null | null | null |
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CA-9_BB_validation
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
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2023
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{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
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10.60732/95c19122
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MD_1024398629573454165794357
| 2024-08-16T15:17:28 |
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PO_6069604095236917948272353
| null | null | null |
[
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[
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CO_7486873534474855323779268
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CA-9_BB_validation
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
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[
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"Gustav Johansson",
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"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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[
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
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MD_1024398629573454165794357
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PO_9798497810875506123842158
| null | null | null |
[
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[
"DS_9cdtww9pcjqd_0",
"DS_fgakfcwhn9zc_0",
"DS_8zft35i5sbgd_0"
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CA-9_BB_validation
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[
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"Gustav Johansson",
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"J. Andreas Larsson",
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Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
"C"
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[
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[
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2023
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[
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CC-BY-4.0
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{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
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10.60732/95c19122
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DS_8zft35i5sbgd_0
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CA-9_BB_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_8zft35i5sbgd_0
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C60
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C
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-1.41556734,
-0.67176176,
2.46314498
],
[
0.18446003,
0.91097476,
-0.44381364
]
] | null |
[
[
7.246915278169133e-22,
-2.6563292718319116e-22,
6.800465277449554e-23
],
[
-2.6563300146281893e-22,
1.8346787783256284e-21,
5.409152398551946e-23
],
[
6.800462282606319e-23,
5.409150881243612e-23,
1.3448626690226585e-23
]
] | null | null | null | -536.436902 | null | 2.948226 | 5.659591 |
{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
|
MD_1024398629573454165794357
| 2024-08-16T14:46:35 |
11959500598924704648366588580209556714816584656808618740387711942826918242368108508559513343695303725586895939642750541385727659422609840986630332364008232
|
PO_1195950059892470464836658
| null | null | null |
[
"BR_training__14574",
"BB_validation__523",
"CA-9_training__33647"
] |
[
"DS_fw7m5d8b0fa9_0",
"DS_9cdtww9pcjqd_0",
"DS_8zft35i5sbgd_0"
] | 2023-12-01T23:56:37 |
7835142209960582937513769555621640930588638722024479143523112436194698690599084459108438224680483673231686322903329840579642811473360306909092925017755029
|
CO_7835142209960582937513769
|
CA-9_BB_validation
|
[
"Daniel Hedman",
"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Binning-binning configurations from CA-9 dataset used during validation step for NNP_BB potential. CA-9 consists of configurations of carbon with curated subsets chosen to test the effects of intentionally choosing dissimilar configurations when training neural network potentials
|
[
"C"
] | 1 | 4,003 | 4,003 | 233,034 | 0 | 4,003 | 0 | 4,003 | 0 | 4,003 | -501.735936 | 10,202.734006 | 0 | 2023-12-01T18:52:50 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
1
] |
CC-BY-4.0
|
{'source-publication': 'https://doi.org/10.1016/j.cartre.2021.100027', 'source-data': 'https://doi.org/10.24435/materialscloud:6h-yj', 'other': None}
|
10.60732/95c19122
|
9987403613029629768726893456954031024119887046898145763926846230248531061270033011778359623539974970922272163569034827090035859539661759104921473348571593
|
DS_8zft35i5sbgd_0
|
CA-9_BB_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_8zft35i5sbgd_0
|
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