chemical_formula_hill
string | chemical_formula_reduced
string | chemical_formula_anonymous
string | atomic_numbers
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list | elements_ratios
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int32 | cell
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list | dimension_types
list | nperiodic_dimensions
int32 | structure_hash
string | multiplicity
int32 | software
string | method
string | adsorption_energy
float64 | atomic_forces
list | atomization_energy
float64 | cauchy_stress
list | cauchy_stress_volume_normalized
bool | electronic_band_gap
float64 | electronic_band_gap_type
string | energy
float64 | formation_energy
float64 | max_force_norm
float64 | mean_force_norm
float64 | property_object_metadata
string | property_object_metadata_id
string | property_object_last_modified
timestamp[ns] | property_object_hash
string | property_object_id
string | configuration_metadata
string | configuration_metadata_id
string | configuration_labels
list | configuration_names
list | configuration_dataset_ids
list | configuration_last_modified
timestamp[ns] | configuration_hash
string | configuration_id
string | dataset_name
string | dataset_authors
list | dataset_description
string | dataset_elements
list | dataset_nelements
int32 | dataset_nproperty_objects
int64 | dataset_nconfigurations
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int64 | dataset_adsorption_energy_count
int64 | dataset_atomic_forces_count
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int64 | dataset_cauchy_stress_count
int64 | dataset_electronic_band_gap_count
int64 | dataset_energy_count
int64 | dataset_energy_mean
float64 | dataset_energy_variance
float64 | dataset_formation_energy_count
int64 | dataset_last_modified
timestamp[ns] | dataset_dimension_types
list | dataset_nperiodic_dimensions
list | dataset_publication_year
string | dataset_total_elements_ratios
list | dataset_license
string | dataset_links
string | dataset_doi
string | dataset_hash
string | dataset_id
string | dataset_extended_id
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ag32
|
Ag
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A
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[
"Ag"
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[
1
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[
true,
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true
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[
1,
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1
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| 1 |
VASP
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DFT-PBE-D3
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[
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] | true | null | null | -72.61647 | null | 0.527564 | 0.999337 |
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|
MD_9985399391223336507104240
| 2024-08-16T15:40:40 |
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|
PO_3214997361346993551407685
| null | null | null |
[
"deepmd_set.000_495"
] |
[
"DS_t0ec1irmeo59_0",
"DS_6e5ljaqa3cfr_0"
] | 2023-12-01T23:16:21 |
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|
CO_8690607261613241593036854
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
1
] |
LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
|
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|
DS_6e5ljaqa3cfr_0
|
Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
|
Ag32
|
Ag
|
A
|
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[
"Ag"
] |
[
1
] | 1 | 32 |
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[
true,
true,
true
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[
1,
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1
] | 3 |
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| 1 |
VASP
|
DFT-PBE-D3
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] | null |
[] | null | null | null | -86.497383 | null | 0.145158 | 0.280426 |
{"input": {"encut": {"value": 650, "units": "eV"}}, "hash": "9985399391223336507104240349147387433243557514633906439105331955381975213318101075814762881954519768656981458682509405813528289710302917162391265942695039", "id": "MD_9985399391223336507104240"}
|
MD_9985399391223336507104240
| 2024-08-16T14:48:30 |
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|
PO_1841698072588696088598144
| null | null | null |
[
"deepmd_set.000_27"
] |
[
"DS_6e5ljaqa3cfr_0"
] | 2023-12-01T23:15:44 |
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|
CO_8698110058311328048005021
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Ag-PBE_MSMSE_2021
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[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
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[
3
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2023
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[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag6
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Ag
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A
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[
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MD_9985399391223336507104240
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PO_8207498186289810730948036
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[
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CO_8704772830283818231172462
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Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
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2023
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[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag16
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[
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VASP
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DFT-PBE-D3
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[] | null | null | null | -42.867367 | null | 0.216688 | 0.404963 |
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MD_9985399391223336507104240
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PO_4792877376324256254088817
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CO_8707469467619147283483045
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
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[
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2023
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[
1
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LGPL-3.0-only
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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A
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DFT-PBE-D3
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[] | null | null | null | -86.82959 | null | 0.088347 | 0.196647 |
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MD_9985399391223336507104240
| 2024-08-16T15:40:40 |
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PO_4827612611813590519816012
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[
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[
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Ag-PBE_MSMSE_2021
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[
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"Ben Xu",
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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[
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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[
1
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Ag-PBE_MSMSE_2021
|
[
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] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
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2023
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[
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LGPL-3.0-only
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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MD_9985399391223336507104240
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MD_9985399391223336507104240
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MD_9985399391223336507104240
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[
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CO_8786886416658300951321975
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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2023
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_1112669220609413946304626
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[
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CO_8807222393563480007944783
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Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
"Ag"
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3
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2023
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[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:30:06 |
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PO_1894664300520435341769148
| null | null | null |
[
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[
"DS_t0ec1irmeo59_0",
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CO_8809799009533932250181643
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
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1
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[
3
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2023
|
[
1
] |
LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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A
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[
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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[
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LGPL-3.0-only
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Ag
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MD_9985399391223336507104240
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[
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CO_8818418447397915421829879
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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[
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2023
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[
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LGPL-3.0-only
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DS_6e5ljaqa3cfr_0
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Ag16
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MD_9985399391223336507104240
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[
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CO_8819788917536989921326520
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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[
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LGPL-3.0-only
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10.60732/93adbc95
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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CO_8850711193218736594046636
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag16
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MD_9985399391223336507104240
| 2024-08-16T15:09:02 |
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[
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CO_8856242151475170214946570
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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[
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LGPL-3.0-only
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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|
MD_9985399391223336507104240
| 2024-08-16T14:31:50 |
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PO_1311658322802410512727231
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[
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[
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CO_8859760985115655255747141
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
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] |
[
3
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2023
|
[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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A
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DFT-PBE-D3
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MD_9985399391223336507104240
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CO_8875027454647288288234448
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Ag-PBE_MSMSE_2021
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[
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"Ben Xu",
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] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
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[
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_3971919858776320829084146
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[
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CO_8880527269609563411410649
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
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[
3
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2023
|
[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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DFT-PBE-D3
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[] | null | null | null | -42.921589 | null | 0.068055 | 0.136043 |
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MD_9985399391223336507104240
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PO_1269003378928453828641010
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CO_8892068015289874028069404
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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[
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2023
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[
1
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LGPL-3.0-only
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10.60732/93adbc95
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Ag16
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Ag
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:13:21 |
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PO_1293718250656070241727855
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[
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CO_8896456496831949143213597
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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[
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2023
|
[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:44:03 |
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PO_5461382851483241292974024
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[
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|
CO_8905004701170234706927058
|
Ag-PBE_MSMSE_2021
|
[
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"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
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[
3
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2023
|
[
1
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:33:15 |
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PO_7262895141454021228110622
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CO_8921451405580583206018624
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
"Ag"
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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Ag16
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Ag
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A
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[
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VASP
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DFT-PBE-D3
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[] | null | null | null | -43.064682 | null | 0.039667 | 0.083548 |
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MD_9985399391223336507104240
| 2024-08-16T14:49:47 |
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PO_9925962603549511829510739
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[
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CO_8924733332928658998516570
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
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[
[
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1
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] |
[
3
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2023
|
[
1
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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|
DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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[
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VASP
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DFT-PBE-D3
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[] | null | null | null | -42.764236 | null | 0.24072 | 0.497726 |
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|
MD_9985399391223336507104240
| 2024-08-16T14:33:22 |
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PO_2422121235408124399052227
| null | null | null |
[
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[
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] | 2023-12-01T23:15:44 |
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|
CO_8924927529194678278987794
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
1
] |
LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
|
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|
DS_6e5ljaqa3cfr_0
|
Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
|
Ag6
|
Ag
|
A
|
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47
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[
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[
1
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[
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| 1 |
VASP
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DFT-PBE-D3
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[
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|
MD_9985399391223336507104240
| 2024-08-16T15:40:32 |
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PO_7201431479280096795588524
| null | null | null |
[
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[
"DS_t0ec1irmeo59_0",
"DS_6e5ljaqa3cfr_0"
] | 2023-12-01T23:16:21 |
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|
CO_8936314524919289417769057
|
Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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DS_6e5ljaqa3cfr_0
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Ag32
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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LGPL-3.0-only
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DS_6e5ljaqa3cfr_0
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Ag6
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Ag
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MD_9985399391223336507104240
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CO_8947223649441595132101010
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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Ag16
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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[
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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LGPL-3.0-only
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Ag32
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MD_9985399391223336507104240
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PO_5875873254538232772734429
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MD_9985399391223336507104240
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[
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CO_8969531333251992093812505
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag12
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Ag
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MD_9985399391223336507104240
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PO_9251349568722196696744002
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[
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CO_8973506021684734787459453
|
Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
3
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2023
|
[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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[] | null | null | null | -42.851162 | null | 0.022576 | 0.037973 |
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MD_9985399391223336507104240
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CO_8981073882716084408821950
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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LGPL-3.0-only
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Ag32
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[] | null | null | null | -86.803017 | null | 0.200987 | 0.392661 |
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MD_9985399391223336507104240
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CO_8983836082563366762248157
|
Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
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LGPL-3.0-only
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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MD_9985399391223336507104240
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CO_8999784756235389941009129
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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[
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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LGPL-3.0-only
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Ag16
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DFT-PBE-D3
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MD_9985399391223336507104240
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[
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CO_9003452687091012429474812
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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LGPL-3.0-only
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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MD_9985399391223336507104240
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[
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MD_9985399391223336507104240
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CO_9018739092402248648320797
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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MD_9985399391223336507104240
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CO_9023289949188157994561640
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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[
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LGPL-3.0-only
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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[] | null | null | null | -43.306335 | null | 0.07866 | 0.102025 |
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MD_9985399391223336507104240
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
| 2024-08-16T15:41:58 |
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PO_1126622854954229523577104
| null | null | null |
[
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[
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CO_9037697306242370950563447
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
1,
1,
1
]
] |
[
3
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2023
|
[
1
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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A
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VASP
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DFT-PBE-D3
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|
MD_9985399391223336507104240
| 2024-08-16T14:54:13 |
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PO_1106771821419187833730320
| null | null | null |
[
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[
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|
CO_9047924641703562065778184
|
Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
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1
]
] |
[
3
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2023
|
[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
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|
DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag6
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Ag
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A
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[
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47
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[
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[
1
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:32:41 |
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PO_5340157397133989187476781
| null | null | null |
[
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[
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|
CO_9053891186060998347329892
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
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1,
1
]
] |
[
3
] |
2023
|
[
1
] |
LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
|
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|
DS_6e5ljaqa3cfr_0
|
Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
|
Ag6
|
Ag
|
A
|
[
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47,
47
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[
"Ag"
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[
1
] | 1 | 6 |
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[
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[
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VASP
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DFT-PBE-D3
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|
MD_9985399391223336507104240
| 2024-08-16T14:57:48 |
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PO_1158735943708385460931766
| null | null | null |
[
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[
"DS_t0ec1irmeo59_0",
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|
CO_9056361070058166065006284
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[] | null | null | null | -43.250656 | null | 0.218213 | 0.481633 |
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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PO_1270264032116021708131001
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[
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CO_9072002857013511006706148
|
Ag-PBE_MSMSE_2021
|
[
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"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
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[
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2023
|
[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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MD_9985399391223336507104240
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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DS_6e5ljaqa3cfr_0
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Ag12
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Ag
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MD_9985399391223336507104240
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PO_8624942100529449730491058
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[
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CO_9094523939775362420655677
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
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[
3
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2023
|
[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag12
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Ag
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A
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:34:42 |
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PO_2193792075683349825147754
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[
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CO_9094523939775362420655677
|
Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
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1
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] |
[
3
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2023
|
[
1
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
|
Ag6
|
Ag
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A
|
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47
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[
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[
1
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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[
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CO_9114351614396129755989620
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
"Ag"
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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Ag16
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Ag
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A
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[] | null | null | null | -43.309059 | null | 0.126009 | 0.186851 |
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MD_9985399391223336507104240
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CO_9114622078568094651237288
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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[] | null | null | null | -43.279068 | null | 0.172235 | 0.261246 |
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MD_9985399391223336507104240
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PO_1150321318565732974258618
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CO_9120781560584153236029357
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Ag-PBE_MSMSE_2021
|
[
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"Ben Xu",
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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[
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LGPL-3.0-only
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag32
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CO_9147101152387760711960468
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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2023
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[
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LGPL-3.0-only
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag-PBE_MSMSE_2021
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[
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MD_9985399391223336507104240
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PO_5135607971761361802541192
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CO_9166526892209210331951852
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
"Ag"
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[
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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MD_9985399391223336507104240
| 2024-08-16T15:36:18 |
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PO_8649889108547604236590987
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[
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CO_9166571537646356161581256
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
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[
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag6
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Ag
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A
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[
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:30:23 |
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PO_9582664552088890978636059
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[
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CO_9171207106852931648447884
|
Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
3
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2023
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[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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[
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[] | null | null | null | -42.900127 | null | 0.04427 | 0.08891 |
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MD_9985399391223336507104240
| 2024-08-16T14:34:57 |
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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Ag16
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Ag
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[
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[] | null | null | null | -43.271885 | null | 0.296439 | 0.451039 |
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MD_9985399391223336507104240
| 2024-08-16T15:00:07 |
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PO_2508483338853546224044191
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CO_9184848231151770510471240
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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[
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LGPL-3.0-only
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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MD_9985399391223336507104240
| 2024-08-16T14:56:50 |
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PO_1206606036167532942376854
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[
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CO_9185341971695559253885988
|
Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
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[
3
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2023
|
[
1
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LGPL-3.0-only
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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[] | null | null | null | -43.316498 | null | 0.106533 | 0.162683 |
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MD_9985399391223336507104240
| 2024-08-16T14:36:16 |
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PO_5270653569106741756846441
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CO_9186413088019442706192353
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
"Ag"
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[
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[
3
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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MD_9985399391223336507104240
| 2024-08-16T14:48:31 |
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PO_5686420127293365808800019
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[
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CO_9190280992165553718343340
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
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[
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3
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag6
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Ag
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A
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_1184888716351806246479679
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[
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CO_9193079763679977046557758
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Ag-PBE_MSMSE_2021
|
[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
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2023
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[
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LGPL-3.0-only
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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[
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MD_9985399391223336507104240
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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2023
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag16
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Ag-PBE_MSMSE_2021
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[
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MD_9985399391223336507104240
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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MD_9985399391223336507104240
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[
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Ag16
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MD_9985399391223336507104240
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[
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CO_9234919161400015276402704
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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[
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LGPL-3.0-only
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MD_9985399391223336507104240
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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2023
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Ag16
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MD_9985399391223336507104240
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[
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CO_9253814991953645757914619
|
Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
3
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2023
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[
1
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LGPL-3.0-only
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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MD_9985399391223336507104240
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[
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CO_9257786922361456222610789
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
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1
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] |
[
3
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2023
|
[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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MD_9985399391223336507104240
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CO_9258870340732201799015889
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Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
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"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
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[
[
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[
3
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2023
|
[
1
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag6
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Ag
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A
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:36:36 |
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PO_6579879497398222497513511
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[
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CO_9259981074658956593399511
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Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
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[
3
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2023
|
[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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[
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:57:33 |
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PO_1775818165721097202227679
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[
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CO_9264240930728949920726526
|
Ag-PBE_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
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[
3
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2023
|
[
1
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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[
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:06:26 |
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PO_8124689093874453178055537
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CO_9278545303195530948264856
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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[
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2023
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[
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
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10.60732/93adbc95
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Ag16
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Ag
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A
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[
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[] | null | null | null | -43.296772 | null | 0.190186 | 0.29404 |
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MD_9985399391223336507104240
| 2024-08-16T15:18:07 |
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PO_8204187979275729298787424
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CO_9281977054689126027481424
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Ag-PBE_MSMSE_2021
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[
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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[
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[
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2023
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[
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LGPL-3.0-only
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag6
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Ag
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A
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:30:19 |
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PO_1030533093589881583182593
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[
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CO_9283534070320858790062772
|
Ag-PBE_MSMSE_2021
|
[
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"Ben Xu",
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Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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[
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] |
[
3
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2023
|
[
1
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LGPL-3.0-only
|
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10.60732/93adbc95
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DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag16
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Ag
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A
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[
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[
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VASP
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DFT-PBE-D3
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|
MD_9985399391223336507104240
| 2024-08-16T15:39:20 |
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PO_6369954049427914198525082
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[
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[
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CO_9285624710994147586444838
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
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1
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] |
[
3
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2023
|
[
1
] |
LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
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|
DS_6e5ljaqa3cfr_0
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Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
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Ag32
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Ag
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A
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[
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true
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[
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VASP
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DFT-PBE-D3
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[
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|
MD_9985399391223336507104240
| 2024-08-16T14:57:38 |
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PO_2507504555719285695412552
| null | null | null |
[
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[
"DS_t0ec1irmeo59_0",
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] | 2023-12-01T23:16:20 |
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|
CO_9292700984201430725462547
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
1
] |
LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
|
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|
DS_6e5ljaqa3cfr_0
|
Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
|
Ag16
|
Ag
|
A
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47,
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[
"Ag"
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[
1
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[
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0
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[
true,
true,
true
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[
1,
1,
1
] | 3 |
9039470783388687662726566585370774545091977706578983431787324138188868557836811358428904068504703475811819386508278240338642797925741823075232856414134871
| 1 |
VASP
|
DFT-PBE-D3
| null |
[
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[
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] | true | null | null | -38.980721 | null | 0.038251 | 0.090492 |
{"input": {"encut": {"value": 650, "units": "eV"}}, "hash": "9985399391223336507104240349147387433243557514633906439105331955381975213318101075814762881954519768656981458682509405813528289710302917162391265942695039", "id": "MD_9985399391223336507104240"}
|
MD_9985399391223336507104240
| 2024-08-16T14:57:38 |
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|
PO_1062049034777399118764001
| null | null | null |
[
"deepmd_set.000_274"
] |
[
"DS_t0ec1irmeo59_0",
"DS_6e5ljaqa3cfr_0"
] | 2023-12-01T23:16:21 |
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|
CO_9297351878401111982579577
|
Ag-PBE_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 7,600 configurations of Ag used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag"
] | 1 | 7,607 | 7,608 | 152,318 | 0 | 7,607 | 0 | 7,607 | 0 | 7,607 | -45.522778 | 602.974047 | 0 | 2023-12-01T18:16:05 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
1
] |
LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=Ag-PBE', 'other': None}
|
10.60732/93adbc95
|
5138693210452209829365705892618202470655986320490504913593738452080525355092859965653687826682820970682707408266815492641443500284077678110278382432481544
|
DS_6e5ljaqa3cfr_0
|
Ag-PBE_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_6e5ljaqa3cfr_0
|
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