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Ag4
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2023-12-01T22:52:18
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CO_8491823553441380572047030
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:30:37
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MD_8328333280534599668480665
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2023-12-01T22:52:18
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CO_6548223217143091571531792
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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2023-12-01T22:52:18
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CO_5775901510378017034139687
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:30:40
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_elastic_B222_dist03_1_0" ]
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2023-12-01T22:52:18
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CO_9647616213326934627621047
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:57:05
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
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2023-12-01T22:52:18
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CO_4437147656377783811956554
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:01:04
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2023-12-01T22:52:18
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CO_1329198878102704450978535
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:38:41
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null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_8_315_6" ]
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2023-12-01T22:52:18
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CO_1147162861982237845835962
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag7
Ag
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MD_1213582242930949697188121
2024-08-16T15:14:52
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_315_5_sc_vacancies_Vac_0_7" ]
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2023-12-01T22:52:18
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CO_5460904292698003011411761
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T15:06:32
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PO_7437737351541469933489892
{"materials-project-id": "mp-8566", "temperature": 1260, "hash": "3607014462430280100943246663438427879436346551450381038823753778253088670965950441956008500589099843141438118981671400718353914148461928019545349757294996", "id": "MD_3607014462430280100943246"}
MD_3607014462430280100943246
null
[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_elastic_B222_dist03_2_11" ]
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2023-12-01T22:52:18
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CO_5352499655342492842451042
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:40:18
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_db110_1260_0" ]
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2023-12-01T22:52:18
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CO_5327099879241185328108126
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:34:15
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MD_9448874345651185153904896
null
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2023-12-01T22:52:18
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CO_1122926817472793217543221
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:58:47
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_9_315_8" ]
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2023-12-01T22:52:18
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CO_7130868268815935663886259
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:24:21
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MD_8328333280534599668480665
null
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2023-12-01T22:52:18
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CO_1790467448041159425128166
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:07:46
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MD_8328333280534599668480665
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2023-12-01T22:52:18
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CO_1099091460196180801409774
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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2024-08-16T14:38:52
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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CO_1082365818948999853066115
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:26:41
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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CO_8461123435027841577681520
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:31:02
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2023-12-01T22:52:18
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CO_5971068613327067496273262
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:12:17
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PO_5831605046647920417845248
{"materials-project-id": "mp-124", "temperature": 1260, "hash": "8328333280534599668480665244495013534205131916250553748395247603575458621133451557343901170867215808609131575955333758669127640608507517902470598063908496", "id": "MD_8328333280534599668480665"}
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[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_0_14" ]
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2023-12-01T22:52:18
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CO_3806769819451390025833490
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag
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MD_1213582242930949697188121
2024-08-16T14:29:37
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_315_5_sc_10" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_7028376773569071165755968
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:20:03
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_2_12" ]
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CO_8355804019342824772875799
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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Ag
A
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MD_1213582242930949697188121
2024-08-16T15:38:19
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PO_3013412738147551141366005
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_elastic_B222_dist03_4_16" ]
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2023-12-01T22:52:18
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CO_9857693574878099317072740
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
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MD_1213582242930949697188121
2024-08-16T15:00:37
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PO_3248881890369816096190804
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MD_8328333280534599668480665
null
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[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1324542377588408262117683
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:26:42
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PO_8403970341733355363657505
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_vacancies_Vac_0_315_16" ]
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2023-12-01T22:52:18
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CO_4960912875555652734488827
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:28:05
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PO_8875299824621131401993790
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MD_1132670352840213955900662
null
[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_10_4" ]
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2023-12-01T22:52:18
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CO_1557777575026599181627188
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:19:14
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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CO_2122261037219471981667839
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag
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null
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MD_1213582242930949697188121
2024-08-16T15:42:29
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_13" ]
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2023-12-01T22:52:18
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CO_8024021272851246337728533
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:13:34
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_0_5" ]
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2023-12-01T22:52:18
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CO_7320831524324616962068469
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:38:20
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MD_3607014462430280100943246
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[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_elastic_B222_dist03_4_14" ]
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2023-12-01T22:52:18
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CO_6056693829844368189257385
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:30:20
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MD_1328667921261992109900361
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[ "Ag_iter_all_Ag_iter2_3_mp-10597_elastic_B222_dist03_8_1260_6" ]
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2023-12-01T22:52:18
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CO_5071240789405505263403895
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T14:49:39
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MD_1328667921261992109900361
null
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2023-12-01T22:52:18
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CO_1972670539237182214730150
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:33:11
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_0_3" ]
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2023-12-01T22:52:18
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CO_1163587940291329381118254
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:17:19
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2023-12-01T22:52:18
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CO_1072746493802719421202699
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:21:33
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_9_4" ]
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2023-12-01T22:52:18
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CO_8997543300747625596555555
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
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MD_1213582242930949697188121
2024-08-16T14:37:38
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null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_4_315_3" ]
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2023-12-01T22:52:18
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CO_5478828656815379595240730
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:58:34
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PO_3573929568934094180244157
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MD_7369907572514802664472459
null
[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_0_16" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1133177230579938216892227
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:39:15
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PO_1303866446855561472372692
{"materials-project-id": "mp-124", "temperature": 1260, "hash": "8328333280534599668480665244495013534205131916250553748395247603575458621133451557343901170867215808609131575955333758669127640608507517902470598063908496", "id": "MD_8328333280534599668480665"}
MD_8328333280534599668480665
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2023-12-01T22:52:18
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CO_5705255736648171843445141
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:21:11
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null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_3_1260_6" ]
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2023-12-01T22:52:18
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CO_1152193510210149572232357
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:34:33
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PO_1024272779232592450867706
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MD_8328333280534599668480665
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2023-12-01T22:52:18
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CO_4523057670928595865562807
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:33:18
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PO_5528845898789693280699177
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MD_1901264063649552057980032
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2023-12-01T22:52:18
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CO_1219294688408339165738844
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T14:14:48
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PO_4100914894617635622545480
{"materials-project-id": "mp-124", "temperature": 315, "hash": "1901264063649552057980032765360091244306129156863244765520539936315517545718139405924156609694941144556195633664429638527201258218040275372883302651202181", "id": "MD_1901264063649552057980032"}
MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_db110_315_12" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1326838040913647433789725
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:44:31
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PO_8935594000479328940109715
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_0_10" ]
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2023-12-01T22:52:18
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CO_8922801205608198264530784
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:25:19
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PO_1070580735380931045721358
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_0_315_2" ]
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2023-12-01T22:52:18
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CO_1955411236742732388606169
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:26:59
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PO_1405033140174990635006107
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_vacancies_Vac_0_9" ]
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2023-12-01T22:52:18
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CO_8242845673689126449626816
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
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MD_1213582242930949697188121
2024-08-16T15:39:26
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PO_1431074226109388602997243
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_11_16" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_6170721808509314741916973
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:16:02
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PO_7988369847402344528197653
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_vacancies_Vac_0_315_15" ]
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2023-12-01T22:52:18
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CO_2796285223469195424095332
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:41:15
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PO_3242025122208576266606330
{"materials-project-id": "mp-989737", "temperature": 1260, "hash": "7369907572514802664472459792656479822350432190284584914985299482512071508250441675821061406089948279795071975091192420951258952297780368277524012689188713", "id": "MD_7369907572514802664472459"}
MD_7369907572514802664472459
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[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_3_1" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1649029349646467723638491
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:46:36
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MD_1901264063649552057980032
null
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2023-12-01T22:52:18
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CO_9749240637164808864597305
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:17:06
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2023-12-01T22:52:18
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CO_2341441038722120697830771
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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2024-08-16T14:40:16
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23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:34:10
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2023-12-01T22:52:18
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CO_1093613844164753710097820
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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2024-08-16T14:54:40
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2023-12-01T22:52:18
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CO_3656907565058857792235771
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
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MD_1213582242930949697188121
2024-08-16T15:34:03
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MD_7937089555795707578009689
null
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2023-12-01T22:52:18
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CO_6612230163835832210496335
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:39:36
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MD_1901264063649552057980032
null
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2023-12-01T22:52:18
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CO_1243519992050086931872100
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:13:59
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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CO_8085456002664359765130044
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:23:22
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PO_1601615222464181936407709
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MD_8328333280534599668480665
null
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2023-12-01T22:52:18
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CO_6766795087044109930255984
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag7
Ag
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MD_1213582242930949697188121
2024-08-16T14:31:59
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_Vac_0_16" ]
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2023-12-01T22:52:18
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CO_1278416170500517872903648
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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Ag
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MD_1213582242930949697188121
2024-08-16T15:19:03
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MD_1303153961966051304389306
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2023-12-01T22:52:18
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CO_3522814082900492467172053
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:56:18
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2023-12-01T22:52:18
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CO_3251795176399063313076320
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:35:35
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PO_1300676607290646757153242
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_elastic_B222_dist03_6_1260_12" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_9280091259343796614434107
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:39:06
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PO_1584420285863972886233129
{"materials-project-id": "mp-10597", "temperature": 1260, "hash": "13286679212619921099003614589661135797502845301679723817575449411011993163331085690675936048892081785590016785954832167051919897906318395360960558655412066", "id": "MD_1328667921261992109900361"}
MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_4_7" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_6986550681786784782062856
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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7,781.558174
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2023-12-01T17:52:28
[ [ 1, 1, 1 ] ]
[ 3 ]
2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag64
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:37:21
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2023-12-01T22:52:18
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CO_6271734474897314089809708
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:06:00
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PO_7092186815485613095725047
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MD_7369907572514802664472459
null
[ "Ag_iter_all_Ag_iter1_0_mp-989737_elastic_B222_dist03_10_1260_5" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1242285495727869318726754
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag4
Ag
A
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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T15:02:17
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PO_1267283933183908802924958
{"materials-project-id": "mp-8566", "temperature": 1260, "hash": "3607014462430280100943246663438427879436346551450381038823753778253088670965950441956008500589099843141438118981671400718353914148461928019545349757294996", "id": "MD_3607014462430280100943246"}
MD_3607014462430280100943246
null
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2023-12-01T22:52:18
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CO_7365471158104358968573534
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:53:08
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PO_1339016391110584387714359
{"materials-project-id": "mp-124", "temperature": 1260, "hash": "8328333280534599668480665244495013534205131916250553748395247603575458621133451557343901170867215808609131575955333758669127640608507517902470598063908496", "id": "MD_8328333280534599668480665"}
MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_10_7" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8274937892689166600164987
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag31
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MD_1213582242930949697188121
2024-08-16T14:14:23
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PO_8741455159876438568326967
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_vacancies_Vac_0_315_3" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1121074737547381615147550
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag
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MD_1213582242930949697188121
2024-08-16T15:29:30
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CO_1852745901496474368155395
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:22:09
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MD_9448874345651185153904896
null
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2023-12-01T22:52:18
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CO_1048211461221529692977046
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
Ag
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MD_1213582242930949697188121
2024-08-16T15:00:30
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_interstitials_FCC2_crowdion_2" ]
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2023-12-01T22:52:18
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23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:13:31
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PO_4890581417715404590441765
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_315_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_0_10" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
9762500200979322086270590403476904237355512617673579101315414824745916337035692005114709529745233938079756861670118426973716885647419147882199427485217023
CO_9762500200979322086270590
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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3,795
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7,781.558174
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2023-12-01T17:52:28
[ [ 1, 1, 1 ] ]
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2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
[ 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47 ]
[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T15:36:49
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PO_9890977825871738840501681
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_11_3" ]
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2023-12-01T22:52:18
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CO_7379404001151987548066947
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:42:21
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PO_5719706076555059615483497
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_elastic_B222_dist03_1_315_2" ]
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2023-12-01T22:52:18
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CO_7486435567859312260155780
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:30:24
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PO_2948303460708212904835603
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_315_5_sc_elastic_B222_dist03_9_13" ]
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2023-12-01T22:52:18
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CO_1111492604864474030526662
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:12:44
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PO_1274386685820190280969809
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_db111_315_3" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1205974145719678729821762
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:45:50
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PO_1095297582283359374421108
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_elastic_B222_dist03_2_0", "Ag_iter_all_Ag_iter0_315_5_sc_elastic_B222_dist03_2_8" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_9743328054307928597560229
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag7
Ag
A
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[ "Ag" ]
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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:29:38
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PO_4283174386649356482280342
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter2_5_sc_vacancies_Vac_0_315_8" ]
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2023-12-01T22:52:18
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CO_3367748625649216764481370
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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3,795
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2023-12-01T17:52:28
[ [ 1, 1, 1 ] ]
[ 3 ]
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[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
Ag
A
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[ "Ag" ]
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2024-08-16T14:13:46
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CO_1203948319508646505241003
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:18:17
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter0_315_0_mp-989737_elastic_B222_dist03_0_4" ]
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2023-12-01T22:52:18
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CO_1769956828092860815158379
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:08:54
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null
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2023-12-01T22:52:18
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CO_6210419334595575084802213
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:21:52
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PO_1340533067916967401676613
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter0_315_0_mp-989737_elastic_B222_dist03_6_2" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_7637756324027348615204646
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:56:19
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PO_1343353541632474541076601
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MD_9448874345651185153904896
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[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_11_315_2" ]
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2023-12-01T22:52:18
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CO_5988065015009211062182509
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag2
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VASP
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MD_1213582242930949697188121
2024-08-16T14:54:51
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PO_7403788254522561138567124
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MD_1328667921261992109900361
null
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2023-12-01T22:52:18
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CO_3605790936216843916696907
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:54:45
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2023-12-01T22:52:18
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CO_8117711199853030785157765
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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2024-08-16T15:16:41
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2023-12-01T22:52:18
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CO_6507660606201379727709925
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:52:59
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MD_3607014462430280100943246
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2023-12-01T22:52:18
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CO_1198101929637853978832478
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
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MD_1213582242930949697188121
2024-08-16T14:11:45
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PO_5126278887855803978475136
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2023-12-01T22:52:18
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CO_2854406303400963777450174
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag7
Ag
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MD_1213582242930949697188121
2024-08-16T14:20:08
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PO_5379669330207016831654004
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter2_5_sc_vacancies_Vac_0_1260_7" ]
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2023-12-01T22:52:18
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CO_5400848753486327501578904
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
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MD_1213582242930949697188121
2024-08-16T14:51:43
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PO_5694480046813485524714005
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter2_0_mp-989737_elastic_B222_dist03_8_315_3" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_4387538135483226803851091
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag64
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A
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MD_1213582242930949697188121
2024-08-16T14:16:10
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2023-12-01T22:52:18
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CO_2388924804598230159227803
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
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MD_1213582242930949697188121
2024-08-16T15:08:43
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PO_1428724580625671945869390
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter2_0_mp-989737_elastic_B222_dist03_6_315_7" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8394021341104847954497332
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:31:56
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PO_7066579465575232615319826
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null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_elastic_B222_dist03_3_7" ]
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2023-12-01T22:52:18
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CO_9900887331759054357746282
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag64
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MD_1213582242930949697188121
2024-08-16T14:20:39
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2023-12-01T22:52:18
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CO_3908136417137016310522558
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag
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VASP
DFT-PBE
null
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2024-08-16T14:19:57
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_8" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_7447320198418803873618491
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:00:27
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2023-12-01T22:52:18
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CO_5016613474477599065056097
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:52:51
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2023-12-01T22:52:18
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CO_5284331822359429197303952
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:07:47
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[ "Ag_iter_all_Ag_iter0_1260_5_sc_elastic_B222_dist03_1_6" ]
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2023-12-01T22:52:18
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CO_8906504715596431459952269
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:14:28
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null
[ "Ag_iter_all_Ag_iter0_315_5_sc_elastic_B222_dist03_4_1" ]
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2023-12-01T22:52:18
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CO_1199580785641580644599971
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T14:35:24
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MD_1132670352840213955900662
null
[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_7_4" ]
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2023-12-01T22:52:18
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CO_5399291392138391885591788
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:44:30
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PO_1065979326573260255663552
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MD_1212537137353939262048417
null
[ "Ag_iter_all_Ag_iter2_3_mp-10597_elastic_B222_dist03_6_315_1" ]
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2023-12-01T22:52:18
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CO_6369142188370999078446428
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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[ "Ag" ]
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VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:34:49
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PO_1451473548288004235113935
{"materials-project-id": "mp-124", "temperature": 1260, "hash": "8328333280534599668480665244495013534205131916250553748395247603575458621133451557343901170867215808609131575955333758669127640608507517902470598063908496", "id": "MD_8328333280534599668480665"}
MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_elastic_B222_dist03_11_1260_15" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_3321952363564577570615186
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0