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MD_1024398629573454165794357
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[
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[
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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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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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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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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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MD_1024398629573454165794357
| 2024-08-16T14:30:53 |
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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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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
| 2024-08-16T15:03:34 |
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PO_9692106325484289966967722
| null | null | null |
[
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[
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"DS_tag5zubl21w8_0",
"DS_07zjrtacjg3z_0",
"DS_8zft35i5sbgd_0"
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CO_8283273747752159502251690
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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}
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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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C71
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C
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VASP
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DFT-PBE
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{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
|
MD_1024398629573454165794357
| 2024-08-16T15:33:53 |
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PO_8120873710587749726887355
| null | null | null |
[
"BR_training__4756",
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[
"DS_fw7m5d8b0fa9_0",
"DS_9cdtww9pcjqd_0",
"DS_8zft35i5sbgd_0"
] | 2023-12-01T23:56:38 |
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|
CO_8286084440685890553381715
|
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"
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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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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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MD_1024398629573454165794357
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[
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[
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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"
] | 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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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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DS_8zft35i5sbgd_0
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CA-9_BB_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_8zft35i5sbgd_0
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C64
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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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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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"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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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
|
[
"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 |
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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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"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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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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[
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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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[
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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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[
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"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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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
| 2024-08-16T15:04:10 |
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PO_2073659287477081674030310
| null | null | null |
[
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[
"DS_fw7m5d8b0fa9_0",
"DS_07zjrtacjg3z_0",
"DS_8zft35i5sbgd_0"
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|
CO_8889954694200648939262918
|
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
|
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MD_1024398629573454165794357
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[
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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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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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[
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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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"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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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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[
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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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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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C50
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MD_1024398629573454165794357
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PO_8121931083695950118790023
| null | null | null |
[
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[
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CO_9254037689229044170646147
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CA-9_BB_validation
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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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{'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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CA-9_BB_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_8zft35i5sbgd_0
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C49
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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"
] | 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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{'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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CA-9_BB_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_8zft35i5sbgd_0
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C50
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C
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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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[
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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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"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
|
[
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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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[
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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
| 2024-08-16T15:35:02 |
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PO_1091618889119431197763213
| null | null | null |
[
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[
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"DS_fgakfcwhn9zc_0",
"DS_8zft35i5sbgd_0"
] | 2023-12-01T23:56:36 |
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CO_9680765998129547974427774
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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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1
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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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MD_1024398629573454165794357
| 2024-08-16T15:37:19 |
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PO_1049027792990685348301000
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[
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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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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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C63
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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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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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[
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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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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
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[
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[
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CO_1008851090437247935378482
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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 |
[
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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}
|
10.60732/95c19122
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DS_8zft35i5sbgd_0
|
CA-9_BB_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_8zft35i5sbgd_0
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C24
|
C
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A
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[
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[
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[
true,
true,
true
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[
1,
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1
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| 1 |
VASP
|
DFT-PBE
| null |
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[
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[
0.27740274,
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] | null |
[
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[
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] | null | null | null | -195.139398 | null | 2.828819 | 6.495666 |
{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
|
MD_1024398629573454165794357
| 2024-08-16T14:13:05 |
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|
PO_9734529759854986948082732
| null | null | null |
[
"BR_validation__1618",
"BB_validation__3582",
"RR_validation__792",
"CA-9_training__29015"
] |
[
"DS_9cdtww9pcjqd_0",
"DS_fgakfcwhn9zc_0",
"DS_mr2qaiqh2sx2_0",
"DS_8zft35i5sbgd_0"
] | 2023-12-01T23:56:38 |
10103968276425098095939275459039184494016607228112939466056608594851525460569896428047119143384538911695386768211016868073268710003384956926200902541473227
|
CO_1010396827642509809593927
|
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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