Datasets:
colabfit
/
23-Single-Element-DNPs_RSCDD_2023-Ag

Dataset card Data Studio Files Community
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2024-08-16T14:48:09
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CO_9417104158118208201824299
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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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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2024-08-16T15:11:08
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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CO_7355288027732828122156969
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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2024-08-16T14:45:29
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MD_1132670352840213955900662
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2023-12-01T22:52:18
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CO_7585388814337741185815342
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_1077448435668930720987779
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
2024-08-16T15:11:24
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_interstitials_FCC2_db111_15" ]
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2023-12-01T22:52:18
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CO_1196292102364942085271252
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
2024-08-16T15:38:33
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PO_8883404620221777840401414
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MD_1132670352840213955900662
null
[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_6_16" ]
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2023-12-01T22:52:18
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CO_7293105937268004050921965
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
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MD_1213582242930949697188121
2024-08-16T14:59:21
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2023-12-01T22:52:18
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CO_2966056045720705969545284
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
2024-08-16T14:40:51
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_elastic_B222_dist03_0_16" ]
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2023-12-01T22:52:18
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CO_3365076278060882327642513
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
2024-08-16T14:24:07
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PO_5379228101608099043192434
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MD_7369907572514802664472459
null
[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_7_12" ]
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2023-12-01T22:52:18
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CO_5642646917416547928818052
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
2024-08-16T14:59:43
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PO_6003678669714063177396865
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MD_1132670352840213955900662
null
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2023-12-01T22:52:18
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CO_9900067380627283834331665
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
2024-08-16T14:53:58
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PO_6997666126010448120845264
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_0_0" ]
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2023-12-01T22:52:18
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CO_6164242829544859567186470
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
Ag33
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:43:15
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MD_8328333280534599668480665
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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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MD_1213582242930949697188121
2024-08-16T15:12:09
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter0_315_0_mp-989737_elastic_B222_dist03_8_5" ]
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2023-12-01T22:52:18
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CO_9595136752549920313434952
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
2024-08-16T14:56:30
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PO_7728990940959580725741820
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MD_7937089555795707578009689
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[ "Ag_iter_all_Ag_iter0_1260_5_sc_vacancies_Vac_0_8" ]
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2023-12-01T22:52:18
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CO_1028385800056527484578615
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
2024-08-16T15:20:50
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PO_1286180931191203132566792
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_interTd_315_0" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1123290845444476882367608
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
[ 47, 47, 47, 47, 47, 47, 47, 47 ]
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MD_1213582242930949697188121
2024-08-16T14:28:00
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PO_1317825751773275742129694
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_0_315_8" ]
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2023-12-01T22:52:18
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CO_7783637365245193907045467
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
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:20:25
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PO_9438898448585160219676747
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_8_15" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1078996205957998659375608
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
[ 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
2024-08-16T15:09:45
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_elastic_B222_dist03_8_6" ]
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2023-12-01T22:52:18
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CO_5969419078002222364159002
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
Ag32
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MD_1213582242930949697188121
2024-08-16T14:40:27
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PO_6384990391747849286355086
{"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_11_0" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8916910601657529134746741
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
Ag
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MD_1213582242930949697188121
2024-08-16T15:31:57
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_315_5_sc_5" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1135986581402610060444023
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
Ag64
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MD_1213582242930949697188121
2024-08-16T14:53:58
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2023-12-01T22:52:18
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CO_9997778901623328682673293
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
2024-08-16T15:39:52
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MD_1132670352840213955900662
null
[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_4_7" ]
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2023-12-01T22:52:18
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CO_8940394501616550556276372
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
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2024-08-16T15:30:58
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2023-12-01T22:52:18
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CO_1170537592532444058641786
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
2024-08-16T15:30:02
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_7" ]
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2023-12-01T22:52:18
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CO_1004594311748305627821127
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
2024-08-16T14:53:04
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PO_6384258622734280136413963
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[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_10_10" ]
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2023-12-01T22:52:18
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CO_1284680799637077471201400
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
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MD_1213582242930949697188121
2024-08-16T15:21:17
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PO_3004606037260199546514723
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_2_5" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1055200999356896613460411
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
Ag32
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:34:33
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PO_4202899138095207418128985
{"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_9_4" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8793739152304191803623398
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 ]
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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
Ag64
Ag
A
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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T14:24:35
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null
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2023-12-01T22:52:18
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CO_3998655298668374728280638
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
Ag4
Ag
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MD_1213582242930949697188121
2024-08-16T14:58:43
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PO_1030879246089411808972085
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MD_3607014462430280100943246
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2023-12-01T22:52:18
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CO_1011028432613388478914511
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
2024-08-16T15:12:04
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MD_7369907572514802664472459
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2023-12-01T22:52:18
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CO_3866778709293134092439001
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
2024-08-16T15:26:55
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MD_3607014462430280100943246
null
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2023-12-01T22:52:18
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CO_6672721522745370987608591
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
Ag31
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:21:28
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2023-12-01T22:52:18
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CO_4641829145022335646444293
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
2024-08-16T15:30:28
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MD_1212537137353939262048417
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2023-12-01T22:52:18
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CO_2342688281461137177445605
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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2024-08-16T14:56:51
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CO_4104425770095810958000251
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
2024-08-16T15:31:52
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[ "Ag_iter_all_Ag_iter0_315_0_mp-989737_elastic_B222_dist03_7_13" ]
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2023-12-01T22:52:18
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CO_1063510988347831504641222
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
2024-08-16T14:45:46
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2023-12-01T22:52:18
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CO_1148708283957692583355695
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
2024-08-16T14:27:32
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PO_4125174686243890622380305
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MD_7369907572514802664472459
null
[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_9_15" ]
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2023-12-01T22:52:18
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CO_2768421578711803590048314
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
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MD_1213582242930949697188121
2024-08-16T14:24:32
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PO_4637720959358341122049341
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_interTd_315_8" ]
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2023-12-01T22:52:18
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CO_1279374816368990475542898
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
Ag64
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MD_1213582242930949697188121
2024-08-16T14:38:14
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_315_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_1_8", "Ag_iter_all_Ag_iter0_1260_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_1_3" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1298599993636204738314708
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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2023
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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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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T15:26:23
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PO_1124734348681368197038512
{"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_14" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_4125510172390229306313038
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
2024-08-16T14:17:24
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PO_1135481178563453969844683
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_interstitials_FCC2_interTd_0" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1305685421843893320098028
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
Ag
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MD_1213582242930949697188121
2024-08-16T14:48:25
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_interstitials_FCC2_db111_16" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_4032598507529065793748775
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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2024-08-16T15:16:25
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2023-12-01T22:52:18
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CO_9143949780579808745231302
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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2024-08-16T14:59:24
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PO_9043074946393284701110633
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2023-12-01T22:52:18
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CO_1032451813207003025361477
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
2024-08-16T14:27:34
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MD_1212537137353939262048417
null
[ "Ag_iter_all_Ag_iter2_3_mp-10597_elastic_B222_dist03_6_315_5" ]
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2023-12-01T22:52:18
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CO_7028842915698305494822514
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
2024-08-16T15:07:45
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_10_315_6" ]
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2023-12-01T22:52:18
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CO_2496705458773973490200727
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
Ag32
Ag
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MD_1213582242930949697188121
2024-08-16T15:08:35
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PO_1210084701211157792342669
{"materials-project-id": "mp-10597", "temperature": 1260, "hash": "13286679212619921099003614589661135797502845301679723817575449411011993163331085690675936048892081785590016785954832167051919897906318395360960558655412066", "id": "MD_1328667921261992109900361"}
MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter2_3_mp-10597_elastic_B222_dist03_8_1260_2" ]
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2023-12-01T22:52:18
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CO_5536949413982910624883155
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
2024-08-16T14:50:40
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2023-12-01T22:52:18
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CO_1280684841060418653456361
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
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_9_0" ]
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2023-12-01T22:52:18
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CO_7912037265742485552163617
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
2024-08-16T15:16:43
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MD_1212537137353939262048417
null
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2023-12-01T22:52:18
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CO_6338154250828511751915707
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
2024-08-16T15:04:45
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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CO_1260182419826137854189437
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
2024-08-16T14:12:32
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MD_7937089555795707578009689
null
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2023-12-01T22:52:18
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CO_1047103691425820844263978
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
2024-08-16T14:57:07
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MD_1328667921261992109900361
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[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_7_7" ]
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2023-12-01T22:52:18
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CO_5763173714892061525857175
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
2024-08-16T15:30:32
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MD_8328333280534599668480665
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2023-12-01T22:52:18
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CO_2438500656958681949075270
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
2024-08-16T14:32:53
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MD_3607014462430280100943246
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2023-12-01T22:52:18
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CO_6573072483634484279291495
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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MD_1213582242930949697188121
2024-08-16T14:54:53
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PO_5363525303896021769889704
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MD_1212537137353939262048417
null
[ "Ag_iter_all_Ag_iter0_315_3_mp-10597_13" ]
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2023-12-01T22:52:18
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CO_5194934817504033434111669
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
2024-08-16T14:19:30
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MD_1212537137353939262048417
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2023-12-01T22:52:18
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CO_1089694986680111733981916
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
2024-08-16T15:25:24
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PO_1100517724383678436132610
{"materials-project-id": "mp-8566", "temperature": 315, "hash": "11326703528402139559006629925880682899840813171508102634762040985168369805329894642619776158735266129511126154804486013599086314589801340094026476560417474", "id": "MD_1132670352840213955900662"}
MD_1132670352840213955900662
null
[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_7_0" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1121351458700564605742314
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
2024-08-16T14:48:50
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_interstitials_FCC2_crowdion_9" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1157929666178288158424856
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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2024-08-16T14:14:11
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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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MD_1213582242930949697188121
2024-08-16T14:24:51
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2023-12-01T22:52:18
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CO_1296607492446836074617534
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
2024-08-16T15:32:25
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PO_3635060809383843311275932
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MD_3607014462430280100943246
null
[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_elastic_B222_dist03_2_2" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1244695830521902578904784
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
Ag32
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MD_1213582242930949697188121
2024-08-16T14:39:13
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PO_3938325245531239431005550
{"materials-project-id": "mp-10597", "temperature": 315, "hash": "12125371373539392620484177675986181439536267581609580449775364043104365556564145989438289935191621476638138105568257359142784084669494018144587940715446536", "id": "MD_1212537137353939262048417"}
MD_1212537137353939262048417
null
[ "Ag_iter_all_Ag_iter0_315_3_mp-10597_elastic_B222_dist03_0_2" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_5242553051493888633213911
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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[ 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
2024-08-16T14:19:40
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2023-12-01T22:52:18
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CO_1919897641120051977471622
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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Ag8
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MD_1213582242930949697188121
2024-08-16T15:34:17
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_9_1260_4" ]
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2023-12-01T22:52:18
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CO_1590802982678318847501845
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
Ag
A
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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T15:20:35
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PO_1092213636229583096569951
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MD_1132670352840213955900662
null
[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_11_10" ]
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2023-12-01T22:52:18
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CO_1012899916569687763225871
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
2024-08-16T14:58:07
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PO_6500562173919619540469949
{"materials-project-id": "mp-124", "temperature": 315, "hash": "1901264063649552057980032765360091244306129156863244765520539936315517545718139405924156609694941144556195633664429638527201258218040275372883302651202181", "id": "MD_1901264063649552057980032"}
MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_elastic_B222_dist03_6_10" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_2780391469209456052924759
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
2024-08-16T14:33:18
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PO_1190868019492050358251676
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_0_315_3" ]
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2023-12-01T22:52:18
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CO_9137493906950846276008428
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
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:38:03
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_elastic_B222_dist03_3_8" ]
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2023-12-01T22:52:18
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CO_1330428652419980939272626
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
2024-08-16T14:33:30
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PO_1321007990136609270167582
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MD_8328333280534599668480665
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[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_8_16" ]
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2023-12-01T22:52:18
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CO_1005430919704004059796026
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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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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CO_2502701802223665027272826
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
2024-08-16T14:45:35
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PO_8588306472149527834799980
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter2_0_mp-989737_elastic_B222_dist03_9_315_4" ]
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2023-12-01T22:52:18
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CO_1641286891698242698197655
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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2023
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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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1
VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:43:41
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PO_5967693751261794685725710
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_6" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8331781363878825798500122
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
Ag32
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MD_1213582242930949697188121
2024-08-16T14:34:19
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PO_1119477904688940406106779
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_11_10" ]
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2023-12-01T22:52:18
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CO_4572211428981459357661948
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
Ag31
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MD_1213582242930949697188121
2024-08-16T14:58:02
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PO_1124837363261446089076572
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MD_1132670352840213955900662
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[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_vacancies_Vac_0_1", "Ag_iter_all_Ag_iter0_315_2_mp-8566_vacancies_Vac_0_14" ]
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2023-12-01T22:52:18
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CO_4113350282989574785639887
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
2024-08-16T15:18:56
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PO_1109411073725614947877855
{"materials-project-id": "mp-989737", "temperature": 315, "hash": "1303153961966051304389306745161979687820769317562912431376859268627918911483247706423830849865130180564570440011238910665293369422487025390606993778282662", "id": "MD_1303153961966051304389306"}
MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter0_315_0_mp-989737_elastic_B222_dist03_9_2" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_2935370948081010175233259
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
Ag64
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:54:31
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null
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2023-12-01T22:52:18
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CO_4581657545706711399342774
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
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VASP
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MD_1213582242930949697188121
2024-08-16T15:32:12
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_7_315_15" ]
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2023-12-01T22:52:18
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CO_1147811956788586913158358
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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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T14:26:11
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PO_1232787282940940039931371
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_7_1260_1" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_3166847463760573152177747
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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A
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2024-08-16T15:09:42
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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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MD_1213582242930949697188121
2024-08-16T15:20:18
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2023-12-01T22:52:18
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CO_1888238536097782393882154
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
2024-08-16T15:25:56
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MD_1212537137353939262048417
null
[ "Ag_iter_all_Ag_iter0_315_3_mp-10597_elastic_B222_dist03_7_9" ]
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2023-12-01T22:52:18
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CO_4530018638732274363854090
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
2024-08-16T15:35:22
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter0_315_0_mp-989737_elastic_B222_dist03_1_9" ]
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2023-12-01T22:52:18
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CO_8237553417894880825062743
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
2024-08-16T15:33:06
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MD_1212537137353939262048417
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[ "Ag_iter_all_Ag_iter2_3_mp-10597_elastic_B222_dist03_8_315_4" ]
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2023-12-01T22:52:18
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CO_1111773679814937852272646
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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1
VASP
DFT-PBE
null
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1.321101
{"input": {"ALGO": "fast", "EDIFF": "1E-8", "ENCUT": "400", "IBRION": "0", "ICHARG": "0", "ISIF": "2", "ISMEAR": "1", "ISTART": "0", "ISYM": "0", "KBLOCK": "10", "KGAMMA": "F", "KPAR": "16", "KSPACING": "0.24", "LCHARG": "T", "LREAL": "F", "LWAVE": "F", "MAXMIX": "50", "NBLOCK": "1", "NELM": "200", "NELMIN": "4", "NPAR": "8", "POTIM": "2", "PREC": "A", "PSTRESS": "0", "SIGMA": "0.15", "SMASS": "-1", "file-type": "INCAR"}, "hash": "12135822429309496971881212100548754870478961791137930949625877367285087883313386750731592539663054471050405358418449513543996992751906584969573924479043013", "id": "MD_1213582242930949697188121"}
MD_1213582242930949697188121
2024-08-16T14:26:21
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PO_5520975349666439587737787
{"materials-project-id": "mp-989737", "temperature": 315, "hash": "1303153961966051304389306745161979687820769317562912431376859268627918911483247706423830849865130180564570440011238910665293369422487025390606993778282662", "id": "MD_1303153961966051304389306"}
MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter2_0_mp-989737_elastic_B222_dist03_7_315_2" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_3416210324417477910826714
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" ]
1
3,795
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104,827
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3,795
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3,795
0
3,795
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7,781.558174
0
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