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chemical_formula_hill
string
chemical_formula_reduced
string
chemical_formula_anonymous
string
atomic_numbers
sequence
elements
sequence
elements_ratios
sequence
nelements
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nsites
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pbc
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multiplicity
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software
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method
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adsorption_energy
float64
atomic_forces
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atomization_energy
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cauchy_stress
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cauchy_stress_volume_normalized
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electronic_band_gap
float64
electronic_band_gap_type
string
energy
float64
formation_energy
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max_force_norm
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mean_force_norm
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property_object_metadata
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property_object_metadata_id
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property_object_last_modified
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property_object_hash
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property_object_id
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configuration_metadata
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configuration_metadata_id
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configuration_labels
sequence
configuration_names
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configuration_dataset_ids
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configuration_last_modified
timestamp[ns]
configuration_hash
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configuration_id
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dataset_authors
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dataset_description
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dataset_elements
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dataset_nelements
int32
dataset_nproperty_objects
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dataset_nconfigurations
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dataset_nsites
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dataset_cauchy_stress_count
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dataset_electronic_band_gap_count
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dataset_energy_count
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dataset_energy_mean
float64
dataset_energy_variance
float64
dataset_formation_energy_count
int64
dataset_last_modified
timestamp[ns]
dataset_dimension_types
sequence
dataset_nperiodic_dimensions
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dataset_publication_year
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dataset_total_elements_ratios
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dataset_license
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dataset_links
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dataset_doi
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dataset_hash
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dataset_id
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dataset_extended_id
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C50
C
A
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1
VASP
DFT-PBE
null
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null
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null
null
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2.965565
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{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
MD_1024398629573454165794357
2024-08-16T14:13:10
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PO_1133526126596838009476204
null
null
null
[ "BR_training__7848", "BB_training__9632", "RR_training__8721", "CA-9_validation__5620" ]
[ "DS_fw7m5d8b0fa9_0", "DS_tag5zubl21w8_0", "DS_l7inbtql4ea9_0", "DS_07zjrtacjg3z_0" ]
2023-12-01T23:58:31
10015420438547329998780248289267683403437296924285540568712667863774686711755402225074675921376755687347231142249764378671481138717896966683970661856810805
CO_1001542043854732999878024
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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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
C71
C
A
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1
VASP
DFT-PBE
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MD_1024398629573454165794357
2024-08-16T14:58:34
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2023-12-01T23:58:31
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CO_1002280152540564963245596
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
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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
2024-08-16T15:11:40
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[ "BR_training__3668", "BB_training__1596", "CA-9_validation__7277" ]
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2023-12-01T23:58:31
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CO_1002704099391520002789264
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
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2023-12-01T18:59:39
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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}
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DS_07zjrtacjg3z_0
CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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null
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MD_1024398629573454165794357
2024-08-16T14:14:32
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PO_6922586782978889212242203
null
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[ "BR_training__5830", "BB_validation__3289", "RR_validation__2483", "CA-9_validation__3422" ]
[ "DS_fw7m5d8b0fa9_0", "DS_07zjrtacjg3z_0", "DS_mr2qaiqh2sx2_0", "DS_8zft35i5sbgd_0" ]
2023-12-01T23:58:30
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CO_1002807178437119090672160
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
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2023-12-01T18:59:39
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2023
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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
CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
C64
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3
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1
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DFT-PBE
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{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
MD_1024398629573454165794357
2024-08-16T15:15:57
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[ "BR_training__10199", "BB_training__18240", "RR_validation__3921", "CA-9_validation__566" ]
[ "DS_fw7m5d8b0fa9_0", "DS_l7inbtql4ea9_0", "DS_mr2qaiqh2sx2_0", "DS_07zjrtacjg3z_0" ]
2023-12-01T23:58:29
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CO_1002978614817417987420088
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
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MD_1024398629573454165794357
2024-08-16T14:12:40
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PO_5202292516448112528439505
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2023-12-01T23:58:31
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CO_1004262963511629500473982
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
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2023-12-01T18:59:39
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DS_07zjrtacjg3z_0
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MD_1024398629573454165794357
2024-08-16T14:30:48
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PO_5098693486289921602497047
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[ "CA-9_validation__5186" ]
[ "DS_07zjrtacjg3z_0" ]
2023-12-01T23:58:30
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CO_1004415904541456014556036
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
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2023-12-01T18:59:39
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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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DS_07zjrtacjg3z_0
CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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MD_1024398629573454165794357
2024-08-16T14:14:16
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[ "BR_training__8122", "BB_training__7291", "CA-9_validation__3876" ]
[ "DS_fw7m5d8b0fa9_0", "DS_l7inbtql4ea9_0", "DS_07zjrtacjg3z_0" ]
2023-12-01T23:58:30
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CO_1005175484871010986337260
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
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2023-12-01T18:59:39
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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}
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DS_07zjrtacjg3z_0
CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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VASP
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MD_1024398629573454165794357
2024-08-16T15:24:42
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2023-12-01T23:58:31
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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
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MD_1024398629573454165794357
2024-08-16T14:34:55
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2023-12-01T23:58:29
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CO_1006738158367626611572222
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
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null
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MD_1024398629573454165794357
2024-08-16T15:25:04
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[ "BR_training__3484", "BB_training__10186", "RR_training__7496", "CA-9_validation__7731" ]
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2023-12-01T23:58:31
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CO_1007696034413804896855895
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
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MD_1024398629573454165794357
2024-08-16T15:01:34
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[ "RR_training__15792", "CA-9_validation__196" ]
[ "DS_07zjrtacjg3z_0", "DS_tag5zubl21w8_0" ]
2023-12-01T23:58:29
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CO_1007946080600495103978782
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
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2023-12-01T18:59:39
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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}
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DS_07zjrtacjg3z_0
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[ true, true, true ]
[ 1, 1, 1 ]
3
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1
VASP
DFT-PBE
null
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null
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null
null
null
-535.314631
null
3.132167
6.6594
{"input": {"encut": {"value": 520, "units": "eV"}}, "hash": "102439862957345416579435757980411251184715859364031590652706556386856859773466490977891980138017845683216054395454090990042136855050809363628328039055230", "id": "MD_1024398629573454165794357"}
MD_1024398629573454165794357
2024-08-16T15:03:32
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PO_2505126487276300903965168
null
null
null
[ "RR_training__8629", "CA-9_validation__6388" ]
[ "DS_07zjrtacjg3z_0", "DS_tag5zubl21w8_0" ]
2023-12-01T23:58:31
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CO_1009578913912419247753061
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
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436,601
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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
C71
C
A
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[ true, true, true ]
[ 1, 1, 1 ]
3
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1
VASP
DFT-PBE
null
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MD_1024398629573454165794357
2024-08-16T14:34:58
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2023-12-01T23:58:31
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CO_1010354021028201718842299
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
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VASP
DFT-PBE
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MD_1024398629573454165794357
2024-08-16T15:25:33
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PO_7724162023549180627144106
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[ "BR_training__8702", "BB_training__17896", "CA-9_validation__7567" ]
[ "DS_fw7m5d8b0fa9_0", "DS_l7inbtql4ea9_0", "DS_07zjrtacjg3z_0" ]
2023-12-01T23:58:31
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CO_1010515369905142514495830
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
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2023-12-01T18:59:39
[ [ 1, 1, 1 ] ]
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2023
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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}
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DS_07zjrtacjg3z_0
CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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MD_1024398629573454165794357
2024-08-16T15:13:29
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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
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MD_1024398629573454165794357
2024-08-16T14:12:40
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2023-12-01T23:58:29
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CO_1012875203383905644218703
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
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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_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
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VASP
DFT-PBE
null
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null
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MD_1024398629573454165794357
2024-08-16T14:51:09
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PO_4006998166626670358250696
null
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[ "RR_training__9146", "CA-9_validation__1049" ]
[ "DS_07zjrtacjg3z_0", "DS_tag5zubl21w8_0" ]
2023-12-01T23:58:29
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CO_1013733175749523837266028
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
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2023-12-01T18:59:39
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2023
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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
CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
C72
C
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1
VASP
DFT-PBE
null
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MD_1024398629573454165794357
2024-08-16T14:28:22
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null
null
null
[ "RR_training__4493", "CA-9_validation__6347" ]
[ "DS_07zjrtacjg3z_0", "DS_tag5zubl21w8_0" ]
2023-12-01T23:58:31
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CO_1015334910620297831559765
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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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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1
VASP
DFT-PBE
null
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null
null
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MD_1024398629573454165794357
2024-08-16T15:17:06
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PO_4464020737446343107830446
null
null
null
[ "BR_training__138", "BB_training__1725", "RR_validation__1833", "CA-9_validation__2742" ]
[ "DS_fw7m5d8b0fa9_0", "DS_l7inbtql4ea9_0", "DS_mr2qaiqh2sx2_0", "DS_07zjrtacjg3z_0" ]
2023-12-01T23:58:30
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CO_1016312856965203366031736
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
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8,000
436,601
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8,000
0
8,000
0
8,000
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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
6786253847045172955885803569588349709236592764831810371069539168969962232135226404189095846670960274765158990683864153553298533309101480717530898583437890
DS_07zjrtacjg3z_0
CA-9_validation__Hedman-Rothe-Johansson-Sandin-Larsson-Miyamoto__DS_07zjrtacjg3z_0
End of preview. Expand in Data Studio

Dataset

CA-9 validation

Description

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

Additional details stored in dataset columns prepended with "dataset_".

Dataset authors

Daniel Hedman, Tom Rothe, Gustav Johansson, Fredrik Sandin, J. Andreas Larsson, Yoshiyuki Miyamoto

Publication

https://doi.org/10.1016/j.cartre.2021.100027

Original data link

https://doi.org/10.24435/materialscloud:6h-yj

License

CC-BY-4.0

Number of unique molecular configurations

8000

Number of atoms

436601

Elements included

C

Properties included

energy, atomic forces, cauchy stress

Cite this dataset

Hedman, D., Rothe, T., Johansson, G., Sandin, F., Larsson, J. A., and Miyamoto, Y. CA-9 validation. ColabFit, 2023. https://doi.org/10.60732/5cebd981

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