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[
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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CA-9_validation
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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_validation
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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10.60732/5cebd981
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DS_07zjrtacjg3z_0
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C71
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MD_1024398629573454165794357
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MD_1024398629573454165794357
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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CA-9_validation
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[
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"Yoshiyuki Miyamoto"
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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{'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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10.60732/5cebd981
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DS_07zjrtacjg3z_0
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CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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C50
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C
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[
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CA-9_validation
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[
"Daniel Hedman",
"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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 | 8,000 | 8,000 | 436,601 | 0 | 8,000 | 0 | 8,000 | 0 | 8,000 | -468.657968 | 12,980.365193 | 0 | 2023-12-01T18:59:39 |
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[
3
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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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10.60732/5cebd981
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DS_07zjrtacjg3z_0
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CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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C59
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MD_1024398629573454165794357
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[
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CO_1215222453486914280326831
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CA-9_validation
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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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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10.60732/5cebd981
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DS_07zjrtacjg3z_0
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CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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C72
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C
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MD_1024398629573454165794357
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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
| 2024-08-16T14:54:03 |
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PO_5867144533369669059343434
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[
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[
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"DS_tag5zubl21w8_0",
"DS_l7inbtql4ea9_0",
"DS_07zjrtacjg3z_0"
] | 2023-12-01T23:58:30 |
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CO_1226953670291128255370676
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CA-9_validation
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[
"Daniel Hedman",
"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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1
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[
3
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2023
|
[
1
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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}
|
10.60732/5cebd981
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DS_07zjrtacjg3z_0
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CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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C72
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C
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DFT-PBE
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{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
|
MD_1024398629573454165794357
| 2024-08-16T14:57:57 |
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PO_9083052239379381613091744
| null | null | null |
[
"CA-9_validation__5402"
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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
| 2024-08-16T14:15:42 |
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PO_1069695878114853114972056
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[
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[
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CO_1234853256587984312379613
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CA-9_validation
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[
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"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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10.60732/5cebd981
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DS_07zjrtacjg3z_0
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CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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C72
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|
MD_1024398629573454165794357
| 2024-08-16T15:17:32 |
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PO_8181545264229765532452094
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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CA-9_validation
|
[
"Daniel Hedman",
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"J. Andreas Larsson",
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] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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
| 2024-08-16T14:54:37 |
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PO_5930074123320262050352697
| null | null | null |
[
"CA-9_validation__1007"
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[
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CO_1239225021606151367931597
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CA-9_validation
|
[
"Daniel Hedman",
"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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
|
[
1
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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}
|
10.60732/5cebd981
|
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DS_07zjrtacjg3z_0
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CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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C71
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C
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{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
|
MD_1024398629573454165794357
| 2024-08-16T15:18:19 |
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PO_7858797110863162344628152
| null | null | null |
[
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[
"DS_07zjrtacjg3z_0",
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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_1040952902565021408079273
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[
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[
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CO_1240195605922474504853469
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CA-9_validation
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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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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10.60732/5cebd981
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DS_07zjrtacjg3z_0
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CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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C71
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|
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MD_1024398629573454165794357
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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"
] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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DS_07zjrtacjg3z_0
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C50
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MD_1024398629573454165794357
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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10.60732/5cebd981
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MD_1024398629573454165794357
| 2024-08-16T14:48:33 |
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PO_1957211711913176438256820
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[
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[
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CO_1250101081231686347541410
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CA-9_validation
|
[
"Daniel Hedman",
"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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 | 8,000 | 8,000 | 436,601 | 0 | 8,000 | 0 | 8,000 | 0 | 8,000 | -468.657968 | 12,980.365193 | 0 | 2023-12-01T18:59:39 |
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[
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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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Configurations from CA-9 dataset used during validation step for NNP_CA-9 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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[
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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] | null |
[
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[
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[
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] | null | null | null | -193.059017 | null | 2.534591 | 5.979171 |
{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
|
MD_1024398629573454165794357
| 2024-08-16T14:56:35 |
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|
PO_1220500675880116333345183
| null | null | null |
[
"BR_training__15387",
"BB_training__11",
"CA-9_validation__2605"
] |
[
"DS_fw7m5d8b0fa9_0",
"DS_l7inbtql4ea9_0",
"DS_07zjrtacjg3z_0"
] | 2023-12-01T23:58:30 |
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|
CO_1254797626333429359950261
|
CA-9_validation
|
[
"Daniel Hedman",
"Tom Rothe",
"Gustav Johansson",
"Fredrik Sandin",
"J. Andreas Larsson",
"Yoshiyuki Miyamoto"
] |
Configurations from CA-9 dataset used during validation step for NNP_CA-9 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 | 8,000 | 8,000 | 436,601 | 0 | 8,000 | 0 | 8,000 | 0 | 8,000 | -468.657968 | 12,980.365193 | 0 | 2023-12-01T18:59:39 |
[
[
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}
|
10.60732/5cebd981
|
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|
DS_07zjrtacjg3z_0
|
CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
|
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