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2024-08-16T14:23:10
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MD_3072275598411872336810647
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2023-12-01T22:58:32
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23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:23:50
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2023-12-01T22:58:32
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CO_2876174955951376977007804
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:16:45
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PO_4193003204877105240871898
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_2899499427177696782611112
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:35:40
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PO_7550235178879066641591485
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MD_8723377259784243212242054
null
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2023-12-01T22:58:32
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CO_2908294642676835604534075
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:10:25
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PO_2501888901714317339002572
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MD_9890234894463978372076872
null
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2023-12-01T22:58:31
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CO_2918109083211544896753756
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:21:29
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2023-12-01T22:58:32
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CO_2919760154753245474230541
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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MD_1213582242930949697188121
2024-08-16T14:44:07
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2023-12-01T22:58:32
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CO_2924075661605545503306585
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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MD_1213582242930949697188121
2024-08-16T15:18:26
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PO_9001725636601106369765874
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2023-12-01T22:58:32
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CO_2934220244162438580597344
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:25:02
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2023-12-01T22:58:32
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CO_2971014280624825013457362
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:26:26
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null
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2023-12-01T22:58:32
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CO_2974472358052173569979144
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:42:22
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_3005826597334862084843231
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:14:31
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PO_3854427732027664333799900
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MD_9890234894463978372076872
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2023-12-01T22:58:31
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CO_3041206462666333441755460
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
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2024-08-16T15:28:19
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MD_1175204308310345149590984
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2023-12-01T22:58:32
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CO_3089506434446941338764653
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:03:09
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MD_5600237606314913062759184
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2023-12-01T22:58:32
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CO_3118638030210195451582005
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:15:19
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PO_7293374864921544619211073
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MD_5459493309020573908757363
null
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2023-12-01T22:58:32
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CO_3123110836824362324612199
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:33:51
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PO_8766733143355594685098141
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MD_9890234894463978372076872
null
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2023-12-01T22:58:32
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CO_3123342571525951993347775
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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GPL-3.0-only
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:12:59
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MD_2164565307674838913500201
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2023-12-01T22:58:32
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CO_3180495820059793315937008
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:43:03
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_3187696620905770164159290
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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
2024-08-16T15:11:05
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PO_1238389330198555261181135
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MD_1189900988700438461574101
null
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2023-12-01T22:58:32
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CO_3209429169876420933154801
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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
2024-08-16T14:15:32
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PO_1093695419278425072684879
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MD_5600237606314913062759184
null
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2023-12-01T22:58:32
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CO_3241529322982940191698110
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:16:29
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PO_2275426784787206492085556
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MD_3072275598411872336810647
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2023-12-01T22:58:32
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CO_3248325513417145136992183
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:11:42
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MD_9890234894463978372076872
null
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2023-12-01T22:58:31
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CO_3258702036883034208730688
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:23:43
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PO_4805228963643983259854190
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MD_8723377259784243212242054
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2023-12-01T22:58:32
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CO_3263723697821000495311836
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:16:29
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PO_7056089481143991514057269
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MD_1226566192249423389047690
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2023-12-01T22:58:32
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CO_3266412165147785938395389
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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2024-08-16T14:17:19
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MD_1175204308310345149590984
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CO_3268290923636856152039057
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:36:50
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MD_2164565307674838913500201
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2023-12-01T22:58:31
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CO_3268986881145303584556672
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:57:18
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PO_3265265701355410009293846
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_3283471527472053772635989
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:21:10
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MD_1271418612909851697008258
null
[ "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_4_14" ]
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2023-12-01T22:58:32
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CO_3307022387690405722015909
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:26:12
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PO_1339365978224257906447287
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MD_1271418612909851697008258
null
[ "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_6_9" ]
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2023-12-01T22:58:32
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CO_3308969246816349234810753
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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2024-08-16T15:35:14
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2023-12-01T22:58:32
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CO_3309224022067804698420019
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:15:17
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2023-12-01T22:58:32
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CO_3325784894523546722730147
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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2024-08-16T15:16:43
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2023-12-01T22:58:32
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CO_3330000727226183161114713
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:53:06
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23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:53:06
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2023-12-01T22:58:32
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23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_1271418612909851697008258
null
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2023-12-01T22:58:32
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CO_3387200962222773626289966
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:01:43
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PO_1232771358140015345638132
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MD_1069713809891562784388190
null
[ "Sb_iter1_1_mp-1179605_930_1" ]
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2023-12-01T22:58:31
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CO_3422739819489240896758323
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:27:09
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PO_4322769206957312057487448
{"materials-project-id": "mp-104", "hash": "11752043083103451495909840591415926271491867612943291451032315583459774104304576606643951090635384335932466416246553743575172220382421067388474766997317180", "id": "MD_1175204308310345149590984"}
MD_1175204308310345149590984
null
[ "Sb_iter0_T232_0_mp-104_vacancies_Vac_0_9" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_3435611828657049233561261
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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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MD_1213582242930949697188121
2024-08-16T15:08:08
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MD_1226566192249423389047690
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2023-12-01T22:58:32
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CO_3483292550412800955304033
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:43:25
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null
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2023-12-01T22:58:32
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CO_3484413020206610695743545
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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MD_1213582242930949697188121
2024-08-16T14:41:44
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PO_3565717523697048180429478
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MD_9890234894463978372076872
null
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2023-12-01T22:58:32
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CO_3505569598637132302487543
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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10.60732/7980ece8
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DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:12:56
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PO_5864899459136817389525211
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MD_1175204308310345149590984
null
[ "Sb_iter0_T930_0_mp-104_elastic_B222_dist03_9_23", "Sb_iter0_T930_0_mp-104_elastic_B222_dist03_9_26" ]
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2023-12-01T22:58:32
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CO_3506231185884163320069554
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:33:42
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PO_3557280030129123139248708
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MD_1329574950964754993516039
null
[ "Sb_iter2_2_mp-133_elastic_B222_dist03_7_930_1" ]
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2023-12-01T22:58:32
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CO_3523441532179297763501048
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb16
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MD_1213582242930949697188121
2024-08-16T14:59:24
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PO_6694156094323499434228258
{"materials-project-id": "mp-7761", "temperature": 232, "hash": "6774213934135675701540773796729302629317554541035381100152130003466711489090000370856816777870328604323851771860481613575171186235492398971819959733875247", "id": "MD_6774213934135675701540773"}
MD_6774213934135675701540773
null
[ "Sb_iter2_6_mp-7761_elastic_B222_dist03_8_232_7" ]
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2023-12-01T22:58:32
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CO_3526288290458325130859592
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:16:51
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2023-12-01T22:58:32
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CO_3559389148712806318820568
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:26:22
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PO_2545423844650297593566552
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MD_5600237606314913062759184
null
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2023-12-01T22:58:32
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CO_3560116307256158079964302
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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
2024-08-16T14:17:42
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MD_1175204308310345149590984
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2023-12-01T22:58:32
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CO_3580905983962800746789937
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:15:25
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PO_1060854706535115237817272
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_3600784134249636590129477
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:37:25
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PO_1246268585243610664643109
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MD_8723377259784243212242054
null
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2023-12-01T22:58:32
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CO_3648703077397599423154766
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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2024-08-16T15:25:59
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[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:56:13
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2023-12-01T22:58:32
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CO_3711655302222045367153865
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:52:32
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MD_1271418612909851697008258
null
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2023-12-01T22:58:32
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CO_3778620360137530423224802
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:02:01
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MD_1271418612909851697008258
null
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2023-12-01T22:58:32
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CO_3810117518566778433223706
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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
2024-08-16T14:46:41
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MD_1226566192249423389047690
null
[ "Sb_iter0_T232_1_mp-1179605_elastic_B222_dist03_0_1" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_3824000856336557546866551
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:45:58
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2023-12-01T22:58:32
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CO_3844954979875188047272580
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:36:24
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PO_1333480241479158965473156
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_3856943024775534993877555
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:38:35
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_3857702055375670035094629
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:15:18
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PO_1195595668318081052409589
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MD_5600237606314913062759184
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2023-12-01T22:58:31
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CO_3858752319210512513452744
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:37:37
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PO_5116033888883941766400295
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MD_1226566192249423389047690
null
[ "Sb_iter0_T232_1_mp-1179605_5" ]
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2023-12-01T22:58:32
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CO_3858871156060082593413822
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:22:06
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PO_8501167639647303610774622
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MD_1271418612909851697008258
null
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2023-12-01T22:58:32
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CO_3916225179916358513793776
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:51:31
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PO_1254826153201659772987064
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MD_8723377259784243212242054
null
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2023-12-01T22:58:32
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CO_3930559081165223212891291
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:30:05
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PO_7623441399897917343359177
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MD_9890234894463978372076872
null
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2023-12-01T22:58:31
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CO_3938632998610235944155630
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:09:13
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2023-12-01T22:58:32
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CO_3975345556264179233558253
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:00:29
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_4027310635659299591687221
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:16:30
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PO_4255170455226756405640617
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MD_6774213934135675701540773
null
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2023-12-01T22:58:31
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CO_4029724838131183210606689
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:23:55
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PO_1286265459283709465037590
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_4048058369786504737326474
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T14:56:50
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2023-12-01T22:58:31
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CO_4102153693991971893805455
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:49:15
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2023-12-01T22:58:32
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CO_4106171305705395125258660
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:35:01
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2023-12-01T22:58:32
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CO_4121636755264642241202893
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:35:01
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CO_4121636755264642241202893
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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2024-08-16T15:35:01
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2023-12-01T22:58:32
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CO_4121636755264642241202893
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:53:14
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PO_5961665114259751496447444
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MD_1329574950964754993516039
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2023-12-01T22:58:32
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CO_4123901952335474173445504
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:11:30
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MD_1271418612909851697008258
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[ "Sb_iter0_T930_11_mp-10630_elastic_B222_dist03_4_1" ]
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CO_4129507137604866506032758
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:28:01
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2023-12-01T22:58:32
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CO_4160448175971997942571698
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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2024-08-16T15:23:49
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_4168667604047581664440158
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:36:02
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2023-12-01T22:58:31
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CO_4197147551098738054811813
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:21:47
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PO_8840997961160323509719351
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MD_1175204308310345149590984
null
[ "Sb_iter0_T232_0_mp-104_elastic_B222_dist03_8_12" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_4238278900617794829399646
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Sb" ]
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5,529
-70.085254
3,545.21839
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2023-12-01T17:58:46
[ [ 1, 1, 1 ] ]
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2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb48
Sb
A
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MD_1213582242930949697188121
2024-08-16T15:38:09
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2023-12-01T22:58:32
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CO_4272856035978802137483765
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:58:14
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2023-12-01T22:58:32
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CO_4290906850120488344981885
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:06:53
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PO_1178481502158289990706429
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MD_1069713809891562784388190
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2023-12-01T22:58:32
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CO_4306092794457950639789616
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:23:40
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CO_4327467209070716239271898
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:02:54
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_4342840001369928614967850
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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2024-08-16T14:18:57
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_4381745947214349289123252
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:11:08
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2023-12-01T22:58:32
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CO_4413561269585283628494535
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:19:44
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MD_1069713809891562784388190
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2023-12-01T22:58:31
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CO_4505290601395558754240822
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
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2023-12-01T22:58:32
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CO_4569316403984923033232734
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:16:47
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PO_9433602775489669700673702
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MD_8723377259784243212242054
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2023-12-01T22:58:32
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CO_4581582698128752490482881
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:26:13
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PO_7232185249458730887255231
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MD_1329574950964754993516039
null
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2023-12-01T22:58:32
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CO_4586677933575277573290709
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:36:30
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PO_1289368090608957245212062
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MD_1175204308310345149590984
null
[ "Sb_iter0_T930_0_mp-104_elastic_B222_dist03_11_12" ]
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2023-12-01T22:58:32
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CO_4593914459367327015842045
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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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MD_1213582242930949697188121
2024-08-16T15:13:42
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PO_5372418637376859273118342
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MD_6774213934135675701540773
null
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2023-12-01T22:58:32
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CO_4596743598558040253393312
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:20:21
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PO_9346733323522661392753792
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MD_1531921544206064124007380
null
[ "Sb_iter0_T232_2_mp-133_elastic_B222_dist03_0_17" ]
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2023-12-01T22:58:31
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CO_4602139550832293651799382
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb17
Sb
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MD_1213582242930949697188121
2024-08-16T15:06:45
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PO_7994546189227119940837861
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MD_6774213934135675701540773
null
[ "Sb_iter2_6_mp-7761_interstitials_BCC2_db100_232_9" ]
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2023-12-01T22:58:32
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CO_4611516631748251529522295
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb7
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MD_1213582242930949697188121
2024-08-16T14:51:49
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PO_3313521552467649404676618
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MD_1329574950964754993516039
null
[ "Sb_iter1_2_mp-133_vacancies_Vac_0_930_5" ]
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2023-12-01T22:58:32
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CO_4621586969358843606463233
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:56:18
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PO_8322380070654840305783733
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MD_6774213934135675701540773
null
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2023-12-01T22:58:31
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CO_4660978353140093983178414
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:14:34
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PO_7072709825498022379465135
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MD_1189900988700438461574101
null
[ "Sb_iter1_0_mp-104_elastic_B222_dist03_2_232_0" ]
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2023-12-01T22:58:32
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CO_4666913806385390100889617
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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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MD_1213582242930949697188121
2024-08-16T14:32:22
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PO_1264978439259597937954443
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MD_1531921544206064124007380
null
[ "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_1_11" ]
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2023-12-01T22:58:32
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CO_4684394181629645210520674
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:18:29
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PO_2184062548536830934481780
{"materials-project-id": "mp-10630", "hash": "12714186129098516970082589363733719283610698297055881320123986092606121232480198725660362258267884797553420912151004146733397963912425401767005473320979214", "id": "MD_1271418612909851697008258"}
MD_1271418612909851697008258
null
[ "Sb_iter0_T930_11_mp-10630_elastic_B222_dist03_6_8" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_4720169164379409677480696
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Sb" ]
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3,545.21839
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2023-12-01T17:58:46
[ [ 1, 1, 1 ] ]
[ 3 ]
2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0