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

Dataset card Data Studio Files Community
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Ni33
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2023-12-01T22:55:26
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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Ni16
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2023-12-01T22:55:26
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_3774511532810433470580689
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:07:02
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2023-12-01T22:55:26
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CO_8845170398780407951211254
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:38:57
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2023-12-01T22:55:26
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CO_7884802502567584311069139
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:16:29
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2023-12-01T22:55:26
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CO_1261604790321790017213430
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:24:08
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MD_6140727495363540633599620
null
[ "Ni_iter0_Ni_iter0_T437_5_mp-1094136_elastic_B222_dist03_1_19" ]
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2023-12-01T22:55:26
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CO_1409440515859610498950702
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:00:52
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MD_7212896525036108519471547
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2023-12-01T22:55:26
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CO_1200422812151536316299717
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T15:09:02
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MD_7254722095552994262685996
null
[ "Ni_iter0_Ni_iter0_T1750_2_mp-1008728_elastic_B222_dist03_8_17" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_5117852678227258365073516
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:38:42
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MD_5254385145730000393819070
null
[ "Ni_iter0_Ni_iter0_T437_1_mp-10257_elastic_B222_dist03_4_8" ]
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2023-12-01T22:55:26
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CO_9664686957469512398757281
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
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MD_1213582242930949697188121
2024-08-16T15:25:31
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MD_5254385145730000393819070
null
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2023-12-01T22:55:26
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CO_4372420248818954589024581
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T14:40:21
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MD_9779790798079339782879715
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2023-12-01T22:55:26
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CO_4507645820128327677659634
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:18:26
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MD_6140727495363540633599620
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2023-12-01T22:55:26
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CO_6789803147716883866183998
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:42:12
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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2023-12-01T22:55:26
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CO_4784638055967944541804424
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:58:20
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2023-12-01T22:55:26
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CO_9957047861923473971989650
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:27:22
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2023-12-01T22:55:26
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:12:15
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PO_3190632444697525367487671
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2023-12-01T22:55:26
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CO_1025480704125819123041257
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:09:59
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PO_1317644810838615460359627
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2023-12-01T22:55:26
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CO_1175043232569439102971120
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T14:43:54
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[ "Ni_iter0_Ni_iter0_T1750_1_mp-10257_elastic_B222_dist03_0_2" ]
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2023-12-01T22:55:26
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CO_2867685039110450147609964
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T15:31:36
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PO_9454773257574523337009344
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MD_1335738535281727543802207
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[ "Ni_iter1_Ni_4_mp-1014111_elastic_B222_dist03_8_1750_4" ]
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2023-12-01T22:55:26
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CO_4512538866270343623123265
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni33
Ni
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MD_1213582242930949697188121
2024-08-16T14:42:55
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MD_1229072388698067718151592
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[ "Ni_iter3_Ni_iter3_0_mp-23_interstitials_FCC2_interTd_1750_3" ]
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2023-12-01T22:55:26
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CO_7464365097051065588260369
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:52:04
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MD_9779790798079339782879715
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2023-12-01T22:55:26
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CO_1623840058784247590607864
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:53:42
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2023-12-01T22:55:26
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CO_2440166936668308349178941
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:23:52
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PO_5720322184942664981764985
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CO_5186352315488849259501120
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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2024-08-16T15:38:57
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2023-12-01T22:55:26
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CO_9716970572852107156992238
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:34:53
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PO_6552511043539984671122094
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2023-12-01T22:55:26
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CO_9796246332196656401395681
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:58:53
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MD_7212896525036108519471547
null
[ "Ni_iter0_Ni_iter0_T437_0_mp-23_interstitials_FCC2_interTd_11" ]
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2023-12-01T22:55:26
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CO_1019632582431798511622618
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:17:16
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MD_7212896525036108519471547
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2023-12-01T22:55:26
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CO_1015360872777920965253740
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/b184fffc
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DS_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T14:24:20
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MD_5254385145730000393819070
null
[ "Ni_iter0_Ni_iter0_T1750_1_mp-10257_elastic_B222_dist03_0_16" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_7467318823799772889672831
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T15:14:29
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2023-12-01T22:55:26
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CO_8325883858769443222680165
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:02:48
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MD_6140727495363540633599620
null
[ "Ni_iter0_Ni_iter0_T1750_5_mp-1094136_elastic_B222_dist03_1_12" ]
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2023-12-01T22:55:26
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CO_1305554937945137455317116
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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2024-08-16T14:36:47
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PO_4386368610604438729553945
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MD_1224209468321307231874454
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[ "Ni_iter3_Ni_iter3_0_mp-23_elastic_B222_dist03_5_437_5" ]
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2023-12-01T22:55:26
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CO_1184620255352997514600191
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T14:49:04
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PO_4497374037646243946344164
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MD_9779790798079339782879715
null
[ "Ni_iter0_Ni_iter0_T437_4_mp-1014111_elastic_B222_dist03_11_16" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_3961636048827867038159547
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:52:21
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MD_7212896525036108519471547
null
[ "Ni_iter0_Ni_iter0_T437_0_mp-23_elastic_B222_dist03_8_15" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_1073519729601500809574477
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni33
Ni
A
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MD_1213582242930949697188121
2024-08-16T15:17:28
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MD_7212896525036108519471547
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2023-12-01T22:55:26
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CO_3635492034829508040181209
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:46:05
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PO_1122277121689159134159011
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MD_4344208784001717795889537
null
[ "Ni_iter1_Ni_4_mp-1014111_elastic_B222_dist03_10_437_6" ]
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2023-12-01T22:55:26
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CO_5823750280139622804697244
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T14:17:38
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PO_1197990831039544592468947
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MD_6140727495363540633599620
null
[ "Ni_iter0_Ni_iter0_T1750_5_mp-1094136_elastic_B222_dist03_3_16" ]
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2023-12-01T22:55:26
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CO_2062026653614449882828092
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:18:00
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PO_1197063337464873092101890
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MD_1229072388698067718151592
null
[ "Ni_iter1_Ni_0_mp-23_elastic_B222_dist03_5_1750_6" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_4416827782453295600031782
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:16:53
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PO_7148641816817846167465288
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MD_1229072388698067718151592
null
[ "Ni_iter1_Ni_0_mp-23_elastic_B222_dist03_9_1750_0" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_1210490229269009285993325
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
A
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:55:26
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:59:49
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2023-12-01T22:55:26
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:57:53
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2023-12-01T22:55:26
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:41:56
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2023-12-01T22:55:26
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CO_9754801441765965945176157
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:24:29
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2023-12-01T22:55:26
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CO_2067152740941166875197436
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:01:11
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CO_6187233851419770702184033
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
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2024-08-16T14:50:01
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2023-12-01T22:55:26
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CO_9655212961712791027660675
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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2024-08-16T15:22:45
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2023-12-01T22:55:26
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CO_3397821970546418095225047
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:14:21
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MD_1476241874063596347438319
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2023-12-01T22:55:26
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CO_3827357000713218800285490
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:30:57
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PO_1743129751032845516922013
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MD_1476241874063596347438319
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2023-12-01T22:55:26
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CO_3023755307145263675954420
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
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MD_1213582242930949697188121
2024-08-16T14:37:59
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PO_1117183666298051820536167
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MD_6140727495363540633599620
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2023-12-01T22:55:26
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CO_2707205933413207981569408
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:44:33
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PO_1129436924520245781721504
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MD_2005025165069104652544104
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[ "Ni_iter1_Ni_2_mp-1008728_elastic_B222_dist03_5_437_4" ]
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2023-12-01T22:55:26
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CO_9306823175291239585557268
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:08:15
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[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_6176938326567855040005919
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:37:44
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[ "Ni_iter0_Ni_iter0_T1750_0_mp-23_interstitials_FCC2_interTd_19" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_8406187343528608354727267
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:52:49
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2023-12-01T22:55:26
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CO_3375216848247475029402526
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:08:15
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2023-12-01T22:55:26
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CO_3304690404556770290476294
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
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MD_1213582242930949697188121
2024-08-16T15:04:36
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2023-12-01T22:55:26
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CO_1132559399977918359449983
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:21:20
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[ "Ni_iter3_Ni_iter3_2_mp-1008728_elastic_B222_dist03_1_1750_1" ]
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CO_1028104862161708860100906
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
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2023-12-01T22:55:26
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CO_4434839525134342531902760
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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2024-08-16T14:23:02
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2023-12-01T22:55:26
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CO_6869773438589872364412186
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:13:35
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MD_1335738535281727543802207
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2023-12-01T22:55:26
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CO_6454954666618929578232088
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni15
Ni
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MD_1213582242930949697188121
2024-08-16T14:38:22
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PO_7083297244043282203503205
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MD_1335738535281727543802207
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2023-12-01T22:55:26
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CO_8182892346201465306075965
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T14:28:48
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PO_1250750152253044295569574
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MD_2005025165069104652544104
null
[ "Ni_iter1_Ni_2_mp-1008728_elastic_B222_dist03_1_437_6" ]
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2023-12-01T22:55:26
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CO_9932669004485991349425644
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T14:18:37
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PO_3651444535962019996067645
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MD_1091355767366046379991581
null
[ "Ni_iter3_Ni_iter3_2_mp-1008728_elastic_B222_dist03_5_1750_1" ]
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2023-12-01T22:55:26
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CO_5323691978839243520343724
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:26:22
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2023-12-01T22:55:26
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CO_1014444899487674084980850
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:55:26
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CO_1239333149743795134785460
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni32
Ni
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MD_1213582242930949697188121
2024-08-16T14:38:21
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MD_7212896525036108519471547
null
[ "Ni_iter0_Ni_iter0_T437_0_mp-23_elastic_B222_dist03_6_1" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_4338357799590080837164040
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ni" ]
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2023-12-01T17:55:36
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/b184fffc
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DS_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni33
Ni
A
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[ "Ni" ]
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MD_1213582242930949697188121
2024-08-16T14:53:28
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MD_7212896525036108519471547
null
[ "Ni_iter0_Ni_iter0_T1750_0_mp-23_interstitials_FCC2_interTd_18" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_3074040876523400080451410
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ni" ]
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
A
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:49:06
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2023-12-01T22:55:26
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CO_5411676331076891014774361
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:14:35
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2023-12-01T22:55:26
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CO_7598907717302119588538435
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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2024-08-16T15:25:56
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:20:35
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2023-12-01T22:55:26
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CO_6078081587434113238460286
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
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MD_1213582242930949697188121
2024-08-16T14:16:12
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PO_1045533145341714669681700
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MD_1335738535281727543802207
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[ "Ni_iter1_Ni_4_mp-1014111_elastic_B222_dist03_5_1750_0" ]
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2023-12-01T22:55:26
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CO_2798919097457307949950543
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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2024-08-16T15:21:02
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2023-12-01T22:55:26
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CO_6575319733075932758976807
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
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MD_1213582242930949697188121
2024-08-16T14:47:05
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2023-12-01T22:55:26
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CO_6575694448228951486839655
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:13:57
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2023-12-01T22:55:26
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CO_1222367692330825731481545
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:00:23
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PO_6671146044842381608490816
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MD_1335738535281727543802207
null
[ "Ni_iter1_Ni_4_mp-1014111_elastic_B222_dist03_4_1750_1" ]
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2023-12-01T22:55:26
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CO_8703960517971966651833755
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:02:01
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MD_7212896525036108519471547
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2023-12-01T22:55:26
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CO_1188768931117756256705168
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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CO_1320278968054558404915035
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:33:30
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2023-12-01T22:55:26
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CO_1332356968062258192325199
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
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2024-08-16T14:21:39
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MD_6140727495363540633599620
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[ "Ni_iter0_Ni_iter0_T437_5_mp-1094136_elastic_B222_dist03_9_19" ]
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2023-12-01T22:55:26
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CO_7458308402630349167112907
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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Ni
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MD_1213582242930949697188121
2024-08-16T14:51:18
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MD_9779790798079339782879715
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2023-12-01T22:55:26
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CO_9703794875158430466849858
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:25:12
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MD_7212896525036108519471547
null
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2023-12-01T22:55:26
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CO_7753609580506596117843178
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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DS_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
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MD_1213582242930949697188121
2024-08-16T14:30:19
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MD_9779790798079339782879715
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[ "Ni_iter0_Ni_iter0_T437_4_mp-1014111_elastic_B222_dist03_4_16" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_1261859948537338496687527
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni32
Ni
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MD_1213582242930949697188121
2024-08-16T14:40:43
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MD_7212896525036108519471547
null
[ "Ni_iter0_Ni_iter0_T437_0_mp-23_elastic_B222_dist03_6_10" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_6377132483991116789578374
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
A
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MD_1213582242930949697188121
2024-08-16T15:17:33
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PO_3484808952138676957606227
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MD_7062696260770034239037540
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[ "Ni_iter1_Ni_1_mp-10257_elastic_B222_dist03_8_1750_5" ]
[ "DS_nue14kckbkdh_0" ]
2023-12-01T22:55:26
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CO_1581126027707771796900331
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:55:36
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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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni32
Ni
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MD_1213582242930949697188121
2024-08-16T14:59:33
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MD_7212896525036108519471547
null
[ "Ni_iter0_Ni_iter0_T437_0_mp-23_elastic_B222_dist03_8_6" ]
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2023-12-01T22:55:26
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CO_8563068353723646264386467
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T15:15:05
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PO_5326061042317691333194525
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MD_1229072388698067718151592
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2023-12-01T22:55:26
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CO_7747708356522975909683108
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni15
Ni
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MD_1213582242930949697188121
2024-08-16T14:38:55
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PO_5618597416290805109217067
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MD_9779790798079339782879715
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[ "Ni_iter0_Ni_iter0_T437_4_mp-1014111_vacancies_Vac_0_17" ]
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2023-12-01T22:55:26
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CO_1156189920754616902286363
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ni" ]
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2023-12-01T17:55:36
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23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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MD_1213582242930949697188121
2024-08-16T14:33:32
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MD_5254385145730000393819070
null
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2023-12-01T22:55:26
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CO_2213157143614089671685243
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T15:26:06
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PO_7853812313337477781043343
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MD_1335738535281727543802207
null
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2023-12-01T22:55:26
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CO_1106296129646211046307458
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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MD_1213582242930949697188121
2024-08-16T15:12:20
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PO_1201023981357390248972953
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MD_9779790798079339782879715
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[ "Ni_iter0_Ni_iter0_T1750_4_mp-1014111_elastic_B222_dist03_7_1" ]
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2023-12-01T22:55:26
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CO_1280954898489405636379141
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
Ni16
Ni
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2024-08-16T15:17:23
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23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:09:32
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2023-12-01T22:55:26
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CO_1708300252786059012950318
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0
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Ni
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MD_1213582242930949697188121
2024-08-16T15:00:25
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2023-12-01T22:55:26
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CO_7542579457395077483542063
23-Single-Element-DNPs_RSCDD_2023-Ni
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ni from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_nue14kckbkdh_0
23-Single-Element-DNPs_RSCDD_2023-Ni__Andolina-Saidi__DS_nue14kckbkdh_0