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

Dataset card Data Studio Files Community
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23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2024-08-16T15:00:27
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2023-12-01T22:52:50
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CO_5330032711242701114401611
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:09:22
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MD_1036163058585410650666857
null
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2023-12-01T22:52:50
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CO_1503745190591786360006703
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:11:44
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PO_6413913710110329145639409
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MD_7937157088987030981692291
null
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2023-12-01T22:52:50
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CO_1118377817465133620070824
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T14:48:14
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2023-12-01T22:52:50
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CO_2661655242288274411353179
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:10:29
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2023-12-01T22:52:51
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CO_1255545435172783714568742
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:25:11
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PO_9656594813464715434733810
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_7289968587616098685630333
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2024-08-16T15:35:19
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CO_3488812104533812599869818
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:11:33
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MD_1054558368679942546114670
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2023-12-01T22:52:50
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CO_1062455691163386097115974
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T15:28:25
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PO_6772598232208047732964148
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_1168037722856014719667351
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:24:58
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CO_8930061853817636563336711
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:53:06
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null
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2023-12-01T22:52:50
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CO_6272998726086514460573296
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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CO_9739046002929688369310047
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2024-08-16T14:39:41
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2023-12-01T22:52:50
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CO_6386012237551748127624507
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:34:11
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PO_7115504220591550349644484
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MD_1054558368679942546114670
null
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2023-12-01T22:52:50
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CO_1015445993231725746179542
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:24:31
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CO_1202573355083904863863240
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2024-08-16T15:17:34
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2023-12-01T22:52:50
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CO_4496704403622219154489872
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2024-08-16T14:23:09
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MD_5400386851347773166444329
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CO_5376225678058878204923015
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:36:16
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2023-12-01T22:52:50
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CO_2008243000296300180388957
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:16:26
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2023-12-01T22:52:50
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CO_1010821554275927110584017
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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CO_3928420428725120334091988
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_1224990378109858997884044
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:05:57
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PO_1303638367266443373110452
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_elastic_B222_dist03_0_14" ]
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2023-12-01T22:52:50
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CO_7639435987657966771279027
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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.
[ "Co" ]
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co8
Co
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MD_1213582242930949697188121
2024-08-16T14:41:32
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MD_6642807180879329290153248
null
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2023-12-01T22:52:50
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CO_5437541144900737953468885
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:12:50
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PO_4913017627344210730317623
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter2_0_mp-54_elastic_B222_dist03_5_1800_6" ]
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2023-12-01T22:52:50
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CO_1180042942633264615910521
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co31
Co
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MD_1213582242930949697188121
2024-08-16T14:30:13
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PO_3071657487751840909748600
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MD_4769414187976683966140502
null
[ "Co_iter_all_Co_iter0_1800_3_mp-102_vacancies_Vac_0_9" ]
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2023-12-01T22:52:50
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CO_7646976529330180887930668
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_8083140888902518022352426
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:19:26
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2023-12-01T22:52:50
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CO_6758680063726492168191049
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:26:21
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MD_5400386851347773166444329
null
[ "Co_iter_all_Co_iter0_450_1_mp-1183710_elastic_B222_dist03_10_7" ]
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2023-12-01T22:52:50
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CO_7544938520205052348037560
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:53:56
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MD_1893387634103462169451603
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2023-12-01T22:52:50
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CO_2565203283929494533789014
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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MD_1213582242930949697188121
2024-08-16T15:05:05
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_8563035776937618811654765
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:44:03
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PO_1051519072432794936538388
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MD_1054558368679942546114670
null
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2023-12-01T22:52:50
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CO_4558863292829350749303888
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2023-12-01T22:52:50
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CO_9275069850496354096918566
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:22:40
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2023-12-01T22:52:51
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CO_1336441543611080108530977
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:25:29
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[ "Co_iter_all_Co_iter0_450_3_mp-102_elastic_B222_dist03_0_10" ]
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2023-12-01T22:52:50
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CO_6803944394950184629035453
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2023-12-01T22:52:50
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CO_1126654161324229541102145
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
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[ "Co_iter_all_Co_iter0_1800_0_mp-54_elastic_B222_dist03_11_5" ]
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2023-12-01T22:52:50
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CO_6794741410566239675943938
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2024-08-16T14:33:28
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MD_1061199478628841031716802
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2023-12-01T22:52:50
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CO_1171489600609734728471376
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:13:18
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_1077363402455265463922898
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:34:42
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MD_1036163058585410650666857
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2023-12-01T22:52:51
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CO_9124934629859094569063734
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:55:54
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MD_1061199478628841031716802
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2023-12-01T22:52:50
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CO_3220738103469083736614041
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:19:43
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MD_5400386851347773166444329
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CO_1913307364652815581960453
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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MD_1213582242930949697188121
2024-08-16T15:25:16
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PO_1417724859936188793397360
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MD_1893387634103462169451603
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2023-12-01T22:52:50
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CO_1022242638363381504899557
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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MD_1213582242930949697188121
2024-08-16T14:20:48
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PO_6417810623357254231416396
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MD_1893387634103462169451603
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CO_1126757918237636184905001
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:49:33
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PO_5299431552280193169768505
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MD_1061199478628841031716802
null
[ "Co_iter_all_Co_iter0_1800_2_mp-1271679_elastic_B222_dist03_5_6" ]
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2023-12-01T22:52:50
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CO_1093068684891112007453906
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:14:36
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MD_6994839348631346930393042
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2023-12-01T22:52:51
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CO_1108018825106019316497635
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2024-08-16T14:40:06
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CO_2589615165016512096711447
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:55:14
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MD_1061199478628841031716802
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2023-12-01T22:52:50
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CO_6331858056250739264839030
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:54:18
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MD_6642807180879329290153248
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2023-12-01T22:52:50
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CO_9805670222450229665793889
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:54:44
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MD_8614748966000713280909781
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2023-12-01T22:52:50
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CO_7874861028821382022874999
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T17:53:02
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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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23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:16:20
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MD_1893387634103462169451603
null
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CO_3394325758334892327629887
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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MD_1213582242930949697188121
2024-08-16T14:37:09
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_1325665156406900124623319
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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MD_1213582242930949697188121
2024-08-16T15:13:22
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PO_1771859292756966667375288
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MD_1061199478628841031716802
null
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2023-12-01T22:52:51
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CO_9728309162664053820068742
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2024-08-16T14:47:08
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MD_1054558368679942546114670
null
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2023-12-01T22:52:50
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CO_5284053148920334423609287
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2024-08-16T14:48:32
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2023-12-01T22:52:50
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CO_1330784503016192995486068
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:01:00
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MD_1893387634103462169451603
null
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2023-12-01T22:52:51
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CO_1045970898696368134517378
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:01:00
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CO_1033681218322350583787105
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:22:45
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MD_5400386851347773166444329
null
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2023-12-01T22:52:50
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CO_9336268796177183240058389
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:37:08
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PO_7112819796393517626369357
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_elastic_B222_dist03_8_8" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:51
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CO_1080408276953440125411621
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T17:53:02
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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}
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:40:11
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MD_1893387634103462169451603
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2023-12-01T22:52:50
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CO_5342847607303419829379232
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_8614748966000713280909781
null
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2023-12-01T22:52:51
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CO_8477325465231660270915386
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T14:58:39
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_interstitials_HCP2_interTdB_17" ]
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2023-12-01T22:52:50
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CO_7161024136771198309170427
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T14:33:35
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PO_3543186227592572206053676
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MD_1893387634103462169451603
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CO_1375405091976610831161079
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:06:38
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PO_6451258278065218419714206
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_4472840919515747034801639
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:41:19
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PO_6311831314626512745958634
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MD_1054558368679942546114670
null
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2023-12-01T22:52:50
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CO_1919940986544199573128330
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
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CO_5823776942795455646008774
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:08:56
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MD_8614748966000713280909781
null
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CO_3682737168732487895201384
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T15:22:44
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2023-12-01T22:52:50
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CO_1000672694739041669503630
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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CO_1279568682845635347154775
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:29:19
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_9457472856725264245403783
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T14:32:02
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MD_5400386851347773166444329
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CO_4367964391673742698621087
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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MD_1213582242930949697188121
2024-08-16T14:24:45
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PO_2402797877894144524663070
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_elastic_B222_dist03_5_7" ]
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2023-12-01T22:52:51
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CO_2178810839664072689079257
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:23:19
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PO_1117351208888091903345771
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MD_7937157088987030981692291
null
[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_elastic_B222_dist03_6_9" ]
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2023-12-01T22:52:51
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CO_9536752257944978105229251
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:15:02
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PO_1927272812022930185649545
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MD_7937157088987030981692291
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2023-12-01T22:52:50
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CO_5095739238147816972637864
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:24:58
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PO_1076195013288947893866464
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_elastic_B222_dist03_9_9" ]
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2023-12-01T22:52:50
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CO_4257628256280640588649058
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2024-08-16T14:17:17
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[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_elastic_B222_dist03_10_12" ]
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CO_1100182297227809765317211
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
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MD_1213582242930949697188121
2024-08-16T14:41:24
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PO_6600772122997765569083751
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_interstitials_HCP2_interTdB_12" ]
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2023-12-01T22:52:50
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CO_2838272021530232420955316
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co31
Co
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MD_1213582242930949697188121
2024-08-16T15:35:42
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PO_7228672654580297544396925
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MD_7937157088987030981692291
null
[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_vacancies_Vac_0_10" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:51
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CO_9779265763278073159001687
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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.
[ "Co" ]
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3,356
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MD_1213582242930949697188121
2024-08-16T15:32:27
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MD_5400386851347773166444329
null
[ "Co_iter_all_Co_iter0_450_1_mp-1183710_elastic_B222_dist03_3_16" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:51
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CO_1258838111341215188372278
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:41:51
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PO_4971943463206925844971519
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MD_7937157088987030981692291
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[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_elastic_B222_dist03_6_1" ]
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2023-12-01T22:52:51
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CO_5300398937850721074413489
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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Co
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2023-12-01T22:52:51
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CO_9301591133011676117969248
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:05:33
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_interstitials_HCP2_crowdionB_8" ]
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2023-12-01T22:52:50
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CO_2975726074381470177459664
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:31:51
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PO_8694841217635428085277165
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_8907577705248783078096126
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:42:44
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PO_2282194759921668557588360
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MD_6994839348631346930393042
null
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2023-12-01T22:52:50
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CO_4626237019812738602089464
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:28:38
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PO_1247382375713620268320285
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MD_7937157088987030981692291
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[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_elastic_B222_dist03_2_13" ]
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2023-12-01T22:52:51
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CO_3813577814531517729122426
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T15:20:58
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PO_6560921792553628228129617
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MD_1054558368679942546114670
null
[ "Co_iter_all_Co_iter0_450_2_mp-1271679_elastic_B222_dist03_3_11" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:50
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CO_1272053072931016766475024
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2024-08-16T14:14:46
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2023-12-01T22:52:50
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CO_1023178646286062146006263
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2023-12-01T22:52:51
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CO_1808409967563847642945617
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
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CO_5807992216154769854446716
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
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[ "Co_iter_all_Co_iter0_450_3_mp-102_elastic_B222_dist03_9_3" ]
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2023-12-01T22:52:50
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CO_8891681499098464688741027
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
A
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MD_1213582242930949697188121
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_interstitials_HCP2_crowdion_0" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:50
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CO_4662039077285028834505960
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co32
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MD_1213582242930949697188121
2024-08-16T15:00:20
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CO_1166451006091252452585491
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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
2024-08-16T15:10:14
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PO_1105247892734319738983635
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_elastic_B222_dist03_9_7" ]
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2023-12-01T22:52:50
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CO_6480018297013229107757209
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:49:48
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MD_4769414187976683966140502
null
[ "Co_iter_all_Co_iter0_1800_3_mp-102_elastic_B222_dist03_7_8" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:51
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CO_5374521911135904340252698
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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_7563860399893869088196911
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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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2023-12-01T22:52:50
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CO_6011561212867480041213989
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:18:04
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PO_8707711327881702906492062
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MD_7937157088987030981692291
null
[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_elastic_B222_dist03_3_10" ]
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2023-12-01T22:52:50
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CO_1029755098920762246816042
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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.
[ "Co" ]
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2023-12-01T17:53:02
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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}
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co8
Co
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1
VASP
DFT-PBE
null
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{"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
2024-08-16T15:34:32
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PO_1317060708229880733474739
{"temperature": 1800, "hash": "10361630585854106506668579538399454085869296204402093833775446177990566115809532826358553244906608467404497601319689425660609873506876629552850820125244918", "id": "MD_1036163058585410650666857"}
MD_1036163058585410650666857
null
[ "Co_iter_all_Co_iter0_1800_7_sc_elastic_B222_dist03_8_15" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:51
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CO_6426383294009987579665884
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co 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.
[ "Co" ]
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2023-12-01T17:53:02
[ [ 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}
10.60732/15bb1dca
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0