chemical_formula_hill
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timestamp[ns] | property_object_hash
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string | dataset_total_elements_ratios
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string | dataset_id
string | dataset_extended_id
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ag6Au26
|
Ag3Au13
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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_8648016581890505824394405
| null | null | null |
[
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[
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|
CO_1000101322693776324337829
|
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
|
{'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
|
Ag10Au6
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Ag5Au3
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A5B3
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:14:20 |
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PO_8502546429357951603198876
| null | null | null |
[
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[
"DS_t0ec1irmeo59_0"
] | 2023-12-01T23:16:20 |
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|
CO_1000296907725463651258976
|
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
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|
DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
Au32
|
Au
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A
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[
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[
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MD_9985399391223336507104240
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CO_1000511067295890365961027
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MD_9985399391223336507104240
| 2024-08-16T15:12:56 |
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PO_1185806756239160524956914
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[
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CO_1000675139866837760597445
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AgAu-nanoalloy_MSMSE_2021
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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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10.60732/a222a0f6
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Ag10Au6
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A5B3
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[
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MD_9985399391223336507104240
| 2024-08-16T14:30:20 |
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PO_1106859785739149655132664
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[
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[
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CO_1000740611680338254442225
|
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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] | 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}
|
10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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Au32
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Au
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A
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MD_9985399391223336507104240
| 2024-08-16T14:12:41 |
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PO_7451654769610672229434438
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[
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[
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] | 2023-12-01T23:25:28 |
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CO_1000891883601109200742133
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AgAu-nanoalloy_MSMSE_2021
|
[
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"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
|
{'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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Ag25Au23
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Ag25Au23
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A25B23
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_1435541889510311421473893
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CO_1000961332328554618009720
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AgAu-nanoalloy_MSMSE_2021
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[
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"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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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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Ag30Au2
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Ag15Au
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A15B
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MD_9985399391223336507104240
| 2024-08-16T15:12:29 |
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PO_9514524125905743880898021
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CO_1000962344971422810109181
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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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Ag27Au5
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Ag27Au5
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A27B5
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MD_9985399391223336507104240
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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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Ag7Au25
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MD_9985399391223336507104240
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CO_1001304496997647267482587
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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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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag8Au24
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AgAu3
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A3B
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MD_9985399391223336507104240
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PO_1483672518490831749643559
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CO_1001361180048158082538423
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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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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag29Au3
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Ag29Au3
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A29B3
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MD_9985399391223336507104240
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PO_1148933922092894964178881
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[
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[
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CO_1001584710115604647786725
|
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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[
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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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Ag13Au3
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Ag13Au3
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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
| 2024-08-16T15:05:40 |
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PO_4395569153738510188659100
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[
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[
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CO_1001677967170951436154605
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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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] | 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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[
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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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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:25:11 |
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PO_1340291102249959083390382
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[
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[
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CO_1001758317146819959988030
|
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
|
[
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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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
Ag12Au4
|
Ag3Au
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A3B
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[
"Ag",
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[
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VASP
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DFT-PBE-D3
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|
MD_9985399391223336507104240
| 2024-08-16T14:12:05 |
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PO_7439976940434475756661061
| null | null | null |
[
"deepmd_set.000_207"
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[
"DS_t0ec1irmeo59_0"
] | 2023-12-01T23:16:21 |
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|
CO_1001820344656246093410534
|
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
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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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Ag23Au9
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Ag23Au9
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A23B9
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MD_9985399391223336507104240
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PO_5065916747300481956861214
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[
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CO_1001901330391356191360081
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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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Au16
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Au
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A
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:14:24 |
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PO_6063023472753515408001240
| null | null | null |
[
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[
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CO_1002023785178019637445856
|
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
|
[
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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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag2Au30
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AgAu15
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A15B
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MD_9985399391223336507104240
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[
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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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Ag7Au
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MD_9985399391223336507104240
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PO_9037228984173267538505609
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[
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[
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CO_1002180306434260411164665
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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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[
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MD_9985399391223336507104240
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PO_7980922004580273542055035
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[
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CO_1002271873731988830833233
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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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[
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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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AgAu15
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AgAu15
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A15B
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MD_9985399391223336507104240
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Ag10Au6
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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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[
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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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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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Ag13Au3
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MD_9985399391223336507104240
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CO_1002457007555826810832264
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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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10.60732/a222a0f6
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Ag30Au2
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Ag15Au
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A15B
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MD_9985399391223336507104240
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PO_2426631781977788506384627
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[
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CO_1002478465372547858552428
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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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Ag28Au4
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Ag7Au
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MD_9985399391223336507104240
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CO_1002583607998073288181009
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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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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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Au16
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Au
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A
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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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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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MD_9985399391223336507104240
| 2024-08-16T15:32:56 |
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PO_4771632877320290696347118
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[
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CO_1002644075881037865971686
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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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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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MD_9985399391223336507104240
| 2024-08-16T14:14:17 |
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PO_5413899464235680062507818
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CO_1002710081277261618226837
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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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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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MD_9985399391223336507104240
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CO_1002731017674927155703734
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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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AgAu15
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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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2023
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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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AgAu31
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AgAu31
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DFT-PBE-D3
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MD_9985399391223336507104240
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CO_1002757596970448313566585
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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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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
| 2024-08-16T14:14:18 |
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PO_8120718954939673881827081
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[
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CO_1002811790528219318927149
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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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[
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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Ag6Au10
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Ag3Au5
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A5B3
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[
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T14:30:45 |
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PO_4596890787174033549244078
| null | null | null |
[
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[
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CO_1002909665769131609833481
|
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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3481311511156556191035265306681170184294725465275752597341925511358567169350018029706492209753559675591025445233267163801275321275902414163540327935897054
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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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A
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[
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[
1
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VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:19:51 |
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PO_3297658875302887966760306
| null | null | null |
[
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[
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|
CO_1003029426078925402826448
|
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
|
{'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
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DS_t0ec1irmeo59_0
|
AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
|
Au16
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Au
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A
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[
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[
1
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[
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| 1 |
VASP
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DFT-PBE-D3
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MD_9985399391223336507104240
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CO_1003087845542286311051473
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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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Ag12Au20
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MD_9985399391223336507104240
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CO_1003257816947103310944906
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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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DS_t0ec1irmeo59_0
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Ag6Au10
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Ag3Au5
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MD_9985399391223336507104240
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[
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CO_1003331709404810088462845
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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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{'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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Ag3Au13
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Ag3Au13
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MD_9985399391223336507104240
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CO_1003542853493780237994112
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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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Ag
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A
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MD_9985399391223336507104240
| 2024-08-16T14:17:29 |
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PO_4293305127407234167608637
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[
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CO_1003585980093456153415697
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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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[
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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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Ag7Au9
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Ag7Au9
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A9B7
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
| 2024-08-16T15:15:28 |
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PO_3112940143233943243004641
| null | null | null |
[
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[
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CO_1003592745316663786337902
|
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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[
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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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Ag3Au13
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Ag3Au13
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A13B3
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_1206053701927469016910435
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CO_1003665579301807651547304
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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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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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Ag2Au14
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AgAu7
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A7B
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MD_9985399391223336507104240
| 2024-08-16T14:57:35 |
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PO_1516380960874323670899970
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[
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CO_1003717115490097950473779
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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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[
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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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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
| 2024-08-16T14:49:14 |
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PO_7901702361052827574929315
| null | null | null |
[
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[
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CO_1003860160700105875125727
|
AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan 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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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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[
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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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PO_6902148415924966068674928
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CO_1004004101231664251638593
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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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Ag27Au5
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MD_9985399391223336507104240
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CO_1004055739789051738059040
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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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Ag28Au4
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Ag7Au
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A7B
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MD_9985399391223336507104240
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PO_2384066037190583561729813
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CO_1004075832715708469057374
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AgAu-nanoalloy_MSMSE_2021
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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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Ag12Au4
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MD_9985399391223336507104240
| 2024-08-16T15:02:33 |
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PO_1037679707213586865780602
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[
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[
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CO_1004131152742555571964950
|
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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{'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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MD_9985399391223336507104240
| 2024-08-16T14:13:27 |
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CO_1004153129329997331188071
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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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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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AgAu15
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AgAu15
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A15B
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MD_9985399391223336507104240
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PO_1339240660059091079045433
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[
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CO_1004207682053849878632012
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AgAu-nanoalloy_MSMSE_2021
|
[
"Yinan Wang",
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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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DS_t0ec1irmeo59_0
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Ag26Au6
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Ag13Au3
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A13B3
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DFT-PBE-D3
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MD_9985399391223336507104240
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CO_1004212089968418245079216
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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.
|
[
"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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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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Ag32
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Ag
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A
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MD_9985399391223336507104240
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CO_1004315700458277917119787
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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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AgAu31
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MD_9985399391223336507104240
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CO_1004323537652383604361818
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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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Ag5Au11
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Ag5Au11
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A11B5
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MD_9985399391223336507104240
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[
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MD_9985399391223336507104240
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PO_4970346211090022101824542
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[
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CO_1004426711810242602801160
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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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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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Au6
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Au
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MD_9985399391223336507104240
| 2024-08-16T14:44:11 |
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[
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CO_1004545317623599919099208
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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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Ag4Au12
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AgAu3
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A3B
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[
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MD_9985399391223336507104240
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AgAu-nanoalloy_MSMSE_2021
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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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AgAu15
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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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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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Au12
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MD_9985399391223336507104240
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PO_6499243187566785649676398
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[
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CO_1005317821509768852026874
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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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{'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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Ag11Au37
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Ag11Au37
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A37B11
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[
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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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Ag6Au26
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Ag3Au13
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MD_9985399391223336507104240
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CO_1005459096622643463540697
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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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Ag12Au4
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Ag3Au
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_1019845931399569658231752
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[
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CO_1005480258207287799871254
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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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[
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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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Ag6Au26
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Ag3Au13
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A13B3
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MD_9985399391223336507104240
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CO_1005572874701436567676115
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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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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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Ag21Au11
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Ag21Au11
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A21B11
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MD_9985399391223336507104240
| 2024-08-16T14:53:50 |
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CO_1005577374003216863782113
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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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Ag19Au5
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Ag19Au5
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MD_9985399391223336507104240
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PO_7880634978303682949899816
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CO_1005577998023282173476986
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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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{'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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AgAu15
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AgAu15
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MD_9985399391223336507104240
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PO_4447596756369724996499955
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[
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CO_1005609431618667602925538
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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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Ag3Au13
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Ag3Au13
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MD_9985399391223336507104240
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PO_6619448052783563841284268
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CO_1005691831860097297087139
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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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DS_t0ec1irmeo59_0
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AgAu-nanoalloy_MSMSE_2021__Wang-Wang-Zhang-Xu-Wang__DS_t0ec1irmeo59_0
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Ag15Au17
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Ag15Au17
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A17B15
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MD_9985399391223336507104240
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PO_4528279127489553301576385
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CO_1005769689293254306341615
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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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10.60732/a222a0f6
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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
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PO_7653003883684489207495150
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[
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CO_1005829449490043291045906
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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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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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MD_9985399391223336507104240
| 2024-08-16T14:55:02 |
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PO_1003614127928605516519668
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[
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CO_1005873900016076926473090
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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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[
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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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Ag16
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Ag
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A
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[
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DFT-PBE-D3
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MD_9985399391223336507104240
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[
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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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Ag11Au5
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MD_9985399391223336507104240
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CO_1006234682339491012048027
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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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Au16
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Au
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MD_9985399391223336507104240
| 2024-08-16T14:53:46 |
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[
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CO_1006271667386769314924010
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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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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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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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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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Ag7Au9
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MD_9985399391223336507104240
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PO_6521562339995824580851895
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CO_1006654240459980002350900
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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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Ag16
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DFT-PBE-D3
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MD_9985399391223336507104240
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CO_1006800561866449283566336
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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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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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Au32
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Au
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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_1006941661597048728422288
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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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Ag18Au14
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Ag9Au7
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A9B7
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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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Ag11Au5
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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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Ag11Au21
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MD_9985399391223336507104240
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CO_1007090983639043467605166
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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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PO_1829178854125007544318769
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CO_1007099914175359775482971
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AgAu-nanoalloy_MSMSE_2021
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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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Ag6Au10
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Ag3Au5
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MD_9985399391223336507104240
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PO_2941334187809899172953977
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CO_1007231588445176621663816
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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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10.60732/a222a0f6
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DS_t0ec1irmeo59_0
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AgAu31
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AgAu31
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A31B
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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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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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Ag10Au6
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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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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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{'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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PO_1334969719641080796847318
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[
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CO_1007669911575071912573206
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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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Ag16
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DFT-PBE-D3
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MD_9985399391223336507104240
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PO_6035962468901065751670439
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[
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CO_1007782410819048258936395
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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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Ag27Au5
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Ag27Au5
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A27B5
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] |
[
true,
true,
true
] |
[
1,
1,
1
] | 3 |
5946355832475768843500940743828030563970318589808335384798967728529182663615121096607574352972178834528110287898979414662575684834425463436582423120220807
| 1 |
VASP
|
DFT-PBE-D3
| null |
[
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[
1.5347677147989909,
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] | null |
[
[
-16.807144981915016,
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],
[
-5.073704195449209,
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[
2.67222378197264,
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-12.565223706005455
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] | true | null | null | -77.038618 | null | 1.446966 | 3.635209 |
{"input": {"encut": {"value": 650, "units": "eV"}}, "hash": "9985399391223336507104240349147387433243557514633906439105331955381975213318101075814762881954519768656981458682509405813528289710302917162391265942695039", "id": "MD_9985399391223336507104240"}
|
MD_9985399391223336507104240
| 2024-08-16T14:44:31 |
1750918134643168926872170715071516262241384686844730382628017085598368350134174693575478856953038869234854625433848306543528447832857268973957898221290038
|
PO_1750918134643168926872170
| null | null | null |
[
"data.633_set.000_2"
] |
[
"DS_t0ec1irmeo59_0"
] | 2023-12-01T23:16:20 |
10079216958532119747441903300327127740254897811897323956776915528825009190069598485895904455010248813487954808641337798158553347792089749870559120868494626
|
CO_1007921695853211974744190
|
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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