chemical_formula_hill
string | chemical_formula_reduced
string | chemical_formula_anonymous
string | atomic_numbers
list | elements
list | elements_ratios
list | nelements
int32 | nsites
int32 | cell
list | positions
list | pbc
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
int32 | dataset_nsites
int64 | dataset_adsorption_energy_count
int64 | dataset_atomic_forces_count
int64 | dataset_atomization_energy_count
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ag12Au20
|
Ag3Au5
|
A5B3
|
[
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[
"Ag",
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] |
[
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[
true,
true,
true
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[
1,
1,
1
] | 3 |
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| 1 |
VASP
|
DFT-PBE-D3
| null |
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],
[
-0.653070226546588,
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] | null |
[
[
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[
-0.33896660444676807,
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] | true | null | null | -103.824527 | null | 0.954872 | 1.437249 |
{"input": {"encut": {"value": 650, "units": "eV"}}, "hash": "9985399391223336507104240349147387433243557514633906439105331955381975213318101075814762881954519768656981458682509405813528289710302917162391265942695039", "id": "MD_9985399391223336507104240"}
|
MD_9985399391223336507104240
| 2024-08-16T15:29:16 |
5771153457186302437279138009635861630181531812601265476756371557902865665742025864889315145640955225645475216022344702530036186104956436752789678849563066
|
PO_5771153457186302437279138
| null | null | null |
[
"data.540_set.000_7"
] |
[
"DS_t0ec1irmeo59_0"
] | 2023-12-01T23:16:20 |
10079898229882687275128082567771512755015110227479663111336985314941712986201277672152100140444003890431817291178358223022578273424785018145822191057530152
|
CO_1007989822988268727512808
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
0.45979784888320346,
0.5402021511167966
] |
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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
|
3481311511156556191035265306681170184294725465275752597341925511358567169350018029706492209753559675591025445233267163801275321275902414163540327935897054
|
DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
Ag7Au25
|
Ag7Au25
|
A25B7
|
[
47,
47,
47,
47,
47,
47,
47,
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79,
79,
79,
79,
79,
79,
79,
79,
79,
79,
79,
79,
79,
79,
79
] |
[
"Ag",
"Au"
] |
[
0.21875,
0.78125
] | 2 | 32 |
[
[
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0
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[
true,
true,
true
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[
1,
1,
1
] | 3 |
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| 1 |
VASP
|
DFT-PBE-D3
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[
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] | true | null | null | -112.217559 | null | 1.035498 | 2.874948 |
{"input": {"encut": {"value": 650, "units": "eV"}}, "hash": "9985399391223336507104240349147387433243557514633906439105331955381975213318101075814762881954519768656981458682509405813528289710302917162391265942695039", "id": "MD_9985399391223336507104240"}
|
MD_9985399391223336507104240
| 2024-08-16T14:14:44 |
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PO_1160907192774886208468392
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[
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CO_1008037567094864479806887
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
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[
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2023
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[
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag2Au14
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AgAu7
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A7B
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:50:19 |
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PO_1314254993758828810195651
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[
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[
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CO_1008119605404645275528970
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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[
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag5Au11
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Ag5Au11
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A11B5
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_4064112735054298073051179
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[
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[
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CO_1008430377305972445010973
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag3Au29
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Ag3Au29
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A29B3
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DFT-PBE-D3
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MD_9985399391223336507104240
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CO_1008605320635139814043949
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag8Au8
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AgAu
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AB
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:31:35 |
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PO_1559496003938059061184191
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[
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[
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CO_1008626599345874896862933
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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[
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag14Au10
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Ag7Au5
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A7B5
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:01:37 |
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PO_1119492807149212924788738
| null | null | null |
[
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[
"DS_t0ec1irmeo59_0"
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|
CO_1008695921730619434535566
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
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[
3
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2023
|
[
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0.5402021511167966
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag25Au7
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Ag25Au7
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A25B7
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:21:54 |
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PO_4492843374753491487785225
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[
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[
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CO_1008718333735999465965350
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
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[
3
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
Ag26Au6
|
Ag13Au3
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A13B3
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VASP
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DFT-PBE-D3
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|
MD_9985399391223336507104240
| 2024-08-16T15:20:28 |
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PO_1309996606092145376838899
| null | null | null |
[
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[
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|
CO_1008739845213784255670971
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
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[
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MD_9985399391223336507104240
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CO_1008824146210361872083644
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_1008853257497496618751091
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag7Au9
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Ag7Au9
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A9B7
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:24:27 |
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PO_3129888085068659018945919
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[
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[
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CO_1008947609988754479557653
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag3Au13
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Ag3Au13
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A13B3
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:58:53 |
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PO_2883416112791392789623031
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[
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CO_1008964997862460746090306
|
AgAu-nanoalloy_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
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] |
[
3
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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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
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3481311511156556191035265306681170184294725465275752597341925511358567169350018029706492209753559675591025445233267163801275321275902414163540327935897054
|
DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_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
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PO_8300491302964500047596575
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CO_1008979556262403121756972
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AgAu-nanoalloy_MSMSE_2021
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[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag2Au14
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AgAu7
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A7B
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:11:24 |
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PO_5342773664321286950187841
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[
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CO_1008981276038064547784582
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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[
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag9Au23
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Ag9Au23
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A23B9
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:22:06 |
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[
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CO_1009154776725056196286463
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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CO_1009169881742015852286233
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AgAu-nanoalloy_MSMSE_2021
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[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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_1009233386266502940293836
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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Ag2Au30
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AgAu15
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MD_9985399391223336507104240
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PO_1256323454938614905007640
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[
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CO_1009481035060199054859121
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag9Au23
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MD_9985399391223336507104240
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CO_1009506998656346487496643
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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Au16
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Au
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MD_9985399391223336507104240
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[
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MD_9985399391223336507104240
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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DS_t0ec1irmeo59_0
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Au12
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Au
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MD_9985399391223336507104240
| 2024-08-16T15:12:46 |
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PO_4169821930506313706296904
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[
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CO_1009798949910170214739599
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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Ag7Au9
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Ag7Au9
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A9B7
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[
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MD_9985399391223336507104240
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[
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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=AgAu-nanoalloy', 'other': None}
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Ag9Au7
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MD_9985399391223336507104240
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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Au16
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MD_9985399391223336507104240
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PO_2238261375219325041994801
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[
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CO_1010214319932790825775413
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag22Au10
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Ag11Au5
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A11B5
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MD_9985399391223336507104240
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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=AgAu-nanoalloy', 'other': None}
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Ag6Au10
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MD_9985399391223336507104240
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PO_6807961148760845215044318
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CO_1010469183927821670401271
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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Ag11Au5
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MD_9985399391223336507104240
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PO_6196215969602579529560433
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[
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CO_1010480974447422594319025
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag32
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Ag
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A
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MD_9985399391223336507104240
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CO_1010606545576143646985439
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag20Au12
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Ag5Au3
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A5B3
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:46:42 |
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PO_2138017251553494066020556
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CO_1010939630781599724623716
|
AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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Ag6Au26
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:15:15 |
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PO_1090429192559227867009821
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[
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[
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CO_1011130040073041363682928
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
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[
3
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2023
|
[
0.45979784888320346,
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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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
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|
DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
Ag33Au15
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Ag11Au5
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A11B5
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:04:15 |
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PO_3485773596841530295060345
| null | null | null |
[
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[
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CO_1011291860392751272629429
|
AgAu-nanoalloy_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag9Au7
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Ag9Au7
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A9B7
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MD_9985399391223336507104240
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PO_1281208163799157284994444
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[
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[
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CO_1011308091632871425809677
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
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] |
[
3
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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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag22Au26
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Ag11Au13
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A13B11
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|
MD_9985399391223336507104240
| 2024-08-16T15:22:44 |
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PO_7648519039462271138077475
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[
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[
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CO_1011342466396703290945943
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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AgAu15
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AgAu15
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A15B
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_1302951795436660812055229
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[
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[
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CO_1011386618748800833768390
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
[
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1,
1
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] |
[
3
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2023
|
[
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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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag12Au36
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AgAu3
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A3B
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MD_9985399391223336507104240
| 2024-08-16T14:29:43 |
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PO_3634616778624678834989580
| null | null | null |
[
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[
"DS_t0ec1irmeo59_0"
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CO_1011583543588178631244691
|
AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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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Approximately 50,000 configurations of Au, Ag and AuAg 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_1011862561467883925088438
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag10Au22
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MD_9985399391223336507104240
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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Ag14Au2
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MD_9985399391223336507104240
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
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Ag31Au
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MD_9985399391223336507104240
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CO_1012153323569287930352001
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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Ag14Au2
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MD_9985399391223336507104240
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CO_1012337668491927730252673
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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Ag16
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Ag
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MD_9985399391223336507104240
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CO_1012516552801981585930732
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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Ag15Au
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Ag15Au
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A15B
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MD_9985399391223336507104240
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PO_8376087729595439701224027
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CO_1012613493589148588277409
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AgAu-nanoalloy_MSMSE_2021
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[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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Au16
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MD_9985399391223336507104240
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PO_1745279189880052656613617
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[
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CO_1012641210613635230124741
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AgAu-nanoalloy_MSMSE_2021
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[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag6Au10
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Ag3Au5
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A5B3
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:47:10 |
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PO_1390485383509191942259094
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[
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CO_1012727831810699099565013
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Au16
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Au
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A
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:53:03 |
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PO_9225046148672342419074505
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[
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[
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CO_1012750647959521983562824
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag13Au19
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Ag13Au19
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A19B13
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:34:12 |
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PO_1061308232027164194278051
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CO_1012800213463439663392293
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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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=AgAu-nanoalloy', 'other': None}
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Au6
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Au
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:14:28 |
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PO_3189591369174990484227338
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[
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CO_1013392469277837798323161
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag21Au27
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Ag7Au9
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A9B7
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MD_9985399391223336507104240
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Au16
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MD_9985399391223336507104240
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PO_1448114357860470239602761
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[
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[
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CO_1013444282606880120193757
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag8Au16
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AgAu2
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MD_9985399391223336507104240
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CO_1013456238044574072755517
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag6Au26
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Ag3Au13
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A13B3
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MD_9985399391223336507104240
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CO_1013554041992925245423921
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AgAu-nanoalloy_MSMSE_2021
|
[
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] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
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LGPL-3.0-only
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_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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PO_7833766289207368933541435
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CO_1013576684915105570955515
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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Ag10Au22
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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
| 2024-08-16T14:57:34 |
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MD_9985399391223336507104240
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CO_1014122107088156496796774
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_1014178569702602591974951
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag29Au19
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Ag29Au19
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:57:02 |
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PO_8603447421096327098375781
| null | null | null |
[
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[
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] | 2023-12-01T23:16:20 |
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CO_1014218387262646057964503
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
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[
3
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2023
|
[
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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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
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|
DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
Ag32
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Ag
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A
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DFT-PBE-D3
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[
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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CO_1014558543480257306161130
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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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{'source-publication': 'https://doi.org/10.48550/arXiv.2108.06232', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=AgAu-nanoalloy', 'other': None}
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Ag10Au6
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MD_9985399391223336507104240
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CO_1014708633847348181717604
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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Ag11Au37
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Ag11Au37
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A37B11
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MD_9985399391223336507104240
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CO_1014736710319985896789226
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AgAu-nanoalloy_MSMSE_2021
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[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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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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=AgAu-nanoalloy', 'other': None}
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_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
| 2024-08-16T14:26:40 |
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PO_1084955060217316000174241
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[
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[
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CO_1014802030329142524767587
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
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1
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] |
[
3
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2023
|
[
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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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag8Au40
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AgAu5
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A5B
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DFT-PBE-D3
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MD_9985399391223336507104240
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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DS_t0ec1irmeo59_0
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Ag16
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MD_9985399391223336507104240
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PO_5727716111261805983326044
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[
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CO_1014901986625511522953474
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag7Au9
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Ag7Au9
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A9B7
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_5985822235385379786127303
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[
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[
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CO_1014976806543848212055124
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
[
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1,
1
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] |
[
3
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2023
|
[
0.45979784888320346,
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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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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Ag10Au6
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Ag5Au3
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A5B3
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_1009838524059612743866707
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[
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CO_1015107608399594744187081
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag8Au8
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AgAu
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AB
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:15:17 |
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PO_7357522164475928734736705
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[
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[
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CO_1015224724549502290120318
|
AgAu-nanoalloy_MSMSE_2021
|
[
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"Linfeng Zhang",
"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
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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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag5Au11
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Ag5Au11
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A11B5
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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
| 2024-08-16T14:13:54 |
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PO_1972308558210144877644690
| null | null | null |
[
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[
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CO_1015287560630921093953865
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
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1
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] |
[
3
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag11Au5
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Ag11Au5
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A11B5
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MD_9985399391223336507104240
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CO_1015349747467194311153453
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AgAu-nanoalloy_MSMSE_2021
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[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Au32
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Au
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A
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MD_9985399391223336507104240
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CO_1015351463445028479925626
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag32Au16
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Ag2Au
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A2B
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MD_9985399391223336507104240
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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
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[
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CO_1015832766218761247582812
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
"Han Wang"
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Au16
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DFT-PBE-D3
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MD_9985399391223336507104240
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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=AgAu-nanoalloy', 'other': None}
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Au6
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MD_9985399391223336507104240
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[
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CO_1016044077509142103823098
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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Ag12Au4
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Ag3Au
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MD_9985399391223336507104240
| 2024-08-16T14:33:10 |
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PO_7180580734960980841331480
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[
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CO_1016073716457901169320202
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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Ag7Au25
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Ag7Au25
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A25B7
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DFT-PBE-D3
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MD_9985399391223336507104240
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CO_1016102417674866701871458
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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Ag24Au8
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MD_9985399391223336507104240
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CO_1016145913933517469133022
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AgAu-nanoalloy_MSMSE_2021
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[
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"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
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LGPL-3.0-only
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Au12
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Au
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A
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MD_9985399391223336507104240
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PO_7022079334992234505919971
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[
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AgAu-nanoalloy_MSMSE_2021
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[
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"Ben Xu",
"Han Wang"
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Approximately 50,000 configurations of Au, Ag and AuAg 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_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag11Au21
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Ag11Au21
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Au16
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CO_1016452970275868545939692
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AgAu-nanoalloy_MSMSE_2021
|
[
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"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag22Au10
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MD_9985399391223336507104240
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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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AgAu-nanoalloy_MSMSE_2021
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Approximately 50,000 configurations of Au, Ag and AuAg 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_1016858129725551564554879
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AgAu-nanoalloy_MSMSE_2021
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[
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MD_9985399391223336507104240
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CO_1016987494525278017417173
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AgAu-nanoalloy_MSMSE_2021
|
[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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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=AgAu-nanoalloy', 'other': None}
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Ag8Au8
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AgAu
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MD_9985399391223336507104240
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PO_1130702758257736245574048
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CO_1017086946187828832223573
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg 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=AgAu-nanoalloy', 'other': None}
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag13Au3
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Ag13Au3
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A13B3
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_9081413838285468248340572
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[
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CO_1017134253304820191366530
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg 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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[
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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=AgAu-nanoalloy', 'other': None}
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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag22Au26
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Ag11Au13
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A13B11
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MD_9985399391223336507104240
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CO_1017178925105182855545820
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AgAu-nanoalloy_MSMSE_2021
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[
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Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag6Au26
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Ag3Au13
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MD_9985399391223336507104240
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CO_1017270628575765564583719
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AgAu-nanoalloy_MSMSE_2021
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[
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] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
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Ag5Au43
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Ag5Au43
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DFT-PBE-D3
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|
MD_9985399391223336507104240
| 2024-08-16T15:25:57 |
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|
PO_1315571768993250313739105
| null | null | null |
[
"data.759_set.000_5"
] |
[
"DS_t0ec1irmeo59_0"
] | 2023-12-01T23:16:21 |
10173139172881470425469688693829147887172838145110112468200213721444811139148075913316116053940461125426246987115888187232185991238138385467561082513057179
|
CO_1017313917288147042546968
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
0.45979784888320346,
0.5402021511167966
] |
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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
|
3481311511156556191035265306681170184294725465275752597341925511358567169350018029706492209753559675591025445233267163801275321275902414163540327935897054
|
DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
Ag14Au2
|
Ag7Au
|
A7B
|
[
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47,
47,
47,
47,
47,
47,
47,
47,
47,
47,
47,
47,
79,
79
] |
[
"Ag",
"Au"
] |
[
0.875,
0.125
] | 2 | 16 |
[
[
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0
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[
0,
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0
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[
0,
0,
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[
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[
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] |
[
true,
true,
true
] |
[
1,
1,
1
] | 3 |
3231725082973841034605742189614488342936858080992563071803066537826030429703895219318693564478368341045874305443683619976521636508243374549486284978413302
| 1 |
VASP
|
DFT-PBE-D3
| null |
[
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[
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[
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] | true | null | null | -49.31732 | null | 0.03566 | 0.052111 |
{"input": {"encut": {"value": 650, "units": "eV"}}, "hash": "9985399391223336507104240349147387433243557514633906439105331955381975213318101075814762881954519768656981458682509405813528289710302917162391265942695039", "id": "MD_9985399391223336507104240"}
|
MD_9985399391223336507104240
| 2024-08-16T14:55:40 |
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|
PO_1623562876038722033261049
| null | null | null |
[
"deepmd_set.000_4"
] |
[
"DS_t0ec1irmeo59_0"
] | 2023-12-01T23:16:21 |
10173795495617801459415685031445544196257840057731324749007623100777795202953534061660971180953178434082240509361004724807422042730412685217362897408194854
|
CO_1017379549561780145941568
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
"Xiaoyang Wang",
"Linfeng Zhang",
"Ben Xu",
"Han Wang"
] |
Approximately 50,000 configurations of Au, Ag and AuAg used as part of a training dataset for a DP-GEN-based ML model for a Ag-Au nanoalloy potential.
|
[
"Ag",
"Au"
] | 2 | 51,766 | 51,771 | 1,188,220 | 0 | 51,766 | 0 | 51,766 | 0 | 51,766 | -68.544468 | 1,402.940203 | 0 | 2023-12-01T18:18:50 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
0.45979784888320346,
0.5402021511167966
] |
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=AgAu-nanoalloy', 'other': None}
|
10.60732/a222a0f6
|
3481311511156556191035265306681170184294725465275752597341925511358567169350018029706492209753559675591025445233267163801275321275902414163540327935897054
|
DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
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