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Zr17
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23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_5168533597487422813848427
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:20:39
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null
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2023-12-01T23:00:32
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CO_8270211137688464752948635
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
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MD_1213582242930949697188121
2024-08-16T15:15:29
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MD_5279706486609828620642959
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2023-12-01T23:00:32
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CO_1310668711373829363645899
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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CO_6383728739044573603054892
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:19:43
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_crowdionB2_16" ]
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2023-12-01T23:00:32
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CO_6640087277456557707411155
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
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MD_1213582242930949697188121
2024-08-16T14:41:46
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PO_1201505312778476917589618
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MD_9402372724898076044637979
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2023-12-01T23:00:32
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CO_2602012071637327518732621
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
Zr
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MD_1213582242930949697188121
2024-08-16T15:37:47
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PO_1228538250256057911084850
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MD_9402372724898076044637979
null
[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_9_14" ]
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2023-12-01T23:00:32
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CO_6517792670140492393208567
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Zr" ]
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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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
Zr
A
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MD_1213582242930949697188121
2024-08-16T14:53:37
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MD_9402372724898076044637979
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[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_9_4" ]
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CO_5927074213200478510043909
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
Zr
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MD_1213582242930949697188121
2024-08-16T14:53:58
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CO_7808570840040015902272306
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
Zr
A
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MD_1213582242930949697188121
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MD_5279706486609828620642959
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CO_1129369974578591127162202
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
Zr
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MD_1213582242930949697188121
2024-08-16T15:25:20
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CO_4283547016356007035410406
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
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MD_1213582242930949697188121
2024-08-16T15:00:24
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PO_9678034194136614737775220
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MD_1242681989026378489058465
null
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2023-12-01T23:00:32
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CO_8587307177299462349714949
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr32
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MD_1213582242930949697188121
2024-08-16T15:17:04
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MD_6922568494354637749731581
null
[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_8_0" ]
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2023-12-01T23:00:32
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CO_1089323170342579759830833
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/efb626b6
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
A
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23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_1322088402643107679419824
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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MD_1213582242930949697188121
2024-08-16T14:35:41
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_1253890147948435272816115
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr15
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[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_1002279415183932860261969
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1055731924224023963324305
null
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CO_1562258644942077662855787
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T14:58:37
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CO_9824521831821786208952430
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:41:40
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2023-12-01T23:00:32
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CO_1483428978768482110405800
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T15:12:42
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MD_1023274440097845504342842
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2023-12-01T23:00:32
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CO_7125868620551735144970977
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
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CO_2390969238015926501676718
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:07:41
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MD_8829392809605781739714239
null
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2023-12-01T23:00:32
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CO_1111875245262342610290337
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:58:24
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MD_1053968927990176692110395
null
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2023-12-01T23:00:31
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CO_8676800298392481478289765
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:55:46
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PO_3689543073964278592074408
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_0_9" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_1736621668401243537625999
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
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MD_1213582242930949697188121
2024-08-16T14:43:18
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CO_3855064313126698817786646
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
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2023-12-01T23:00:32
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CO_8741969329298056817536546
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
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MD_1213582242930949697188121
2024-08-16T14:23:52
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_6872687749322662356375328
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
Zr
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MD_1213582242930949697188121
2024-08-16T14:55:48
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MD_5279706486609828620642959
null
[ "Zr_iter0_T550_3_mp-41_elastic_B222_dist03_6_15" ]
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2023-12-01T23:00:32
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CO_2550830427773722418538883
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
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MD_1213582242930949697188121
2024-08-16T14:40:08
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PO_5934495681066257572105685
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MD_8829392809605781739714239
null
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2023-12-01T23:00:32
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CO_6788219697825956800116530
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
Zr
A
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MD_1213582242930949697188121
2024-08-16T14:12:42
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PO_1089995610954248505459203
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MD_5279706486609828620642959
null
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2023-12-01T23:00:32
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CO_1080912023855683649840334
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
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2024-08-16T15:32:05
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CO_1306679783120782618411885
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:49:47
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_interOh_12" ]
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2023-12-01T23:00:32
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CO_8675327793244264937120616
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
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MD_1213582242930949697188121
2024-08-16T14:46:29
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MD_2794717748642297120678119
null
[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_4_550_4" ]
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2023-12-01T23:00:32
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CO_1079785181774025018998589
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
Zr
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MD_1213582242930949697188121
2024-08-16T14:56:37
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MD_2794717748642297120678119
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[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_8_550_7" ]
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2023-12-01T23:00:32
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CO_1313525498573671634504068
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
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MD_1213582242930949697188121
2024-08-16T15:10:38
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_3232531357721689735102472
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:12:07
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2023-12-01T23:00:32
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CO_3015893006782004133716068
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr15
Zr
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MD_1213582242930949697188121
2024-08-16T14:33:44
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PO_1267293179304551632935974
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MD_5279706486609828620642959
null
[ "Zr_iter0_T550_3_mp-41_vacancies_Vac_0_33" ]
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2023-12-01T23:00:32
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CO_1042320529535377339678215
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
Zr
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2024-08-16T15:17:47
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2023-12-01T23:00:32
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CO_9979193552245173989497463
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:19:25
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_8_9" ]
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2023-12-01T23:00:31
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CO_5909611155854505644006677
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
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2024-08-16T15:27:09
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PO_3683174436768250784832521
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MD_2794717748642297120678119
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2023-12-01T23:00:32
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CO_3700064091231834216112533
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:15:28
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PO_3718197899144524493885630
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MD_9402372724898076044637979
null
[ "Zr_iter0_T1300_4_mp-1056376_elastic_B222_dist03_4_4" ]
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2023-12-01T23:00:32
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CO_5105887602409624012758668
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:40:13
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null
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CO_7866866644231248422871946
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:24:25
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2023-12-01T23:00:32
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CO_7959868114678434455433636
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:55:03
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MD_9402372724898076044637979
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2023-12-01T23:00:32
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CO_6818740510849596799468400
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T15:39:11
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MD_9402372724898076044637979
null
[ "Zr_iter0_T550_4_mp-1056376_elastic_B222_dist03_0_10" ]
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2023-12-01T23:00:32
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CO_7263883837194670849909413
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
Zr
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MD_1213582242930949697188121
2024-08-16T15:41:25
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PO_1987025552889795583300309
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_11_2" ]
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2023-12-01T23:00:32
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CO_7649548168588267513960274
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
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MD_1213582242930949697188121
2024-08-16T15:21:33
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PO_1133806457811373010282684
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MD_1055731924224023963324305
null
[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_crowdionB_11" ]
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2023-12-01T23:00:32
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CO_2525521002891510479826897
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
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MD_1213582242930949697188121
2024-08-16T15:21:43
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PO_1347104060972547894670070
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MD_1055731924224023963324305
null
[ "Zr_iter0_T1300_0_mp-131_interstitials_HCP2_dbB_0", "Zr_iter2_0_mp-131_interstitials_HCP2_dbB_5" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_1587100546383475082992171
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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MD_1213582242930949697188121
2024-08-16T15:23:13
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MD_1055731924224023963324305
null
[ "Zr_iter0_T1300_0_mp-131_interstitials_HCP2_crowdionB_3" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_2037577363397390210007807
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr32
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MD_1213582242930949697188121
2024-08-16T14:47:05
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MD_6922568494354637749731581
null
[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_1_18" ]
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2023-12-01T23:00:32
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CO_4686168523845495024707124
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
A
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MD_1213582242930949697188121
2024-08-16T15:07:13
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MD_1055731924224023963324305
null
[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_interOh_13" ]
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2023-12-01T23:00:32
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CO_4717239236050169578204808
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Zr" ]
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/efb626b6
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DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:14:34
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MD_1055731924224023963324305
null
[ "Zr_iter0_T1300_0_mp-131_3", "Zr_iter2_0_mp-131_9" ]
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2023-12-01T23:00:32
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CO_3383650014048373215824995
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
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MD_1213582242930949697188121
2024-08-16T15:18:04
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{"materials-project-id": "mp-131", "temperature": 2200, "hash": "12426819890263784890584659996990131482681021214171217212790324473523902146685867354213608051322489143234082633784465177310601188924777179692339607114687491", "id": "MD_1242681989026378489058465"}
MD_1242681989026378489058465
null
[ "Zr_iter3_0_mp-131_interstitials_HCP2_db_2200_0" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_3127048799382968546771863
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Zr" ]
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/efb626b6
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr15
Zr
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MD_1213582242930949697188121
2024-08-16T14:45:03
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PO_6296198113545873290454125
{"materials-project-id": "mp-41", "temperature": 550, "hash": "10539689279901766921103958151337593810612786392286303945991917163681535615164090356044795418184718718667381762150740473780609144029379283606842991702488904", "id": "MD_1053968927990176692110395"}
MD_1053968927990176692110395
null
[ "Zr_iter3_3_mp-41_vacancies_Vac_0_550_5" ]
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2023-12-01T23:00:32
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CO_4986271587627541380817850
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Zr" ]
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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/efb626b6
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
A
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23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:15:53
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2023-12-01T23:00:32
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CO_1310590971752284203466503
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:54:56
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PO_1211672752142084438403443
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CO_8294284842999606054514745
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:59:13
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MD_1055731924224023963324305
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CO_1158643071859644851390929
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:07:47
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2023-12-01T23:00:32
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CO_7072361369306129878173984
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
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2024-08-16T14:41:36
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2023-12-01T23:00:32
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CO_4471264691378047579971053
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T14:45:22
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CO_6975452330200361157037432
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:55:38
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2023-12-01T23:00:32
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CO_1296801532487584166359463
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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2024-08-16T14:25:13
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2023-12-01T23:00:32
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CO_8638867549021506962988547
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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CO_1199050993328940739072287
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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CO_6529593959180456033666650
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
Zr
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MD_1213582242930949697188121
2024-08-16T15:25:29
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PO_7048673368203311777228768
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MD_9402372724898076044637979
null
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2023-12-01T23:00:32
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CO_1308100563710840310667763
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:48:41
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_8393123046783414024349286
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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MD_1213582242930949697188121
2024-08-16T15:38:54
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PO_3207675119298790710924542
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MD_1242681989026378489058465
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2023-12-01T23:00:32
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CO_8643665204976131240751987
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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MD_1213582242930949697188121
2024-08-16T14:30:37
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MD_1242681989026378489058465
null
[ "Zr_iter3_0_mp-131_interstitials_HCP2_interTdB_2200_3" ]
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2023-12-01T23:00:32
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CO_2267642071499229812337342
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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MD_1213582242930949697188121
2024-08-16T15:07:57
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PO_9243653306635810483468085
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MD_1055731924224023963324305
null
[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_interOhB_5" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_1183303088374167897973660
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr8
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MD_1213582242930949697188121
2024-08-16T15:29:40
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PO_9222136702159330840745583
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MD_2794717748642297120678119
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[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_10_550_4" ]
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2023-12-01T23:00:32
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CO_1195443813758149790295097
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr32
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2024-08-16T15:24:47
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2023-12-01T23:00:32
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CO_4475830866976074495960028
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:44:12
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PO_5481761532198215529002057
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2023-12-01T23:00:32
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CO_8079313668101805078460277
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
Zr
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MD_1213582242930949697188121
2024-08-16T14:51:17
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PO_5462392271137925643918621
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_7_4" ]
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2023-12-01T23:00:32
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CO_4409053550663116427981209
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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MD_1213582242930949697188121
2024-08-16T15:01:00
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PO_5955833558737660636512846
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_db_4" ]
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2023-12-01T23:00:32
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CO_6944723750047888285100421
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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2024-08-16T15:17:27
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[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_0_2200_9" ]
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2023-12-01T23:00:32
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CO_1492176883194358338915820
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:46:13
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MD_9402372724898076044637979
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2023-12-01T23:00:32
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CO_8633611527483356172227569
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:35:07
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PO_1424252620966630603098760
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MD_1242681989026378489058465
null
[ "Zr_iter3_0_mp-131_elastic_B222_dist03_3_2200_9" ]
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2023-12-01T23:00:32
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CO_1281854069516662803280905
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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CO_1265010000078798833644240
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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CO_9195677995845658063150565
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:06:52
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2023-12-01T23:00:32
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CO_1296214777249340881011319
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
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[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_0_14" ]
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2023-12-01T23:00:32
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CO_5227767856705853358426462
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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2024-08-16T14:42:41
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MD_5279706486609828620642959
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2023-12-01T23:00:32
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CO_5785028700346012965825960
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
Zr
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MD_1213582242930949697188121
2024-08-16T15:32:14
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_1095996694199691433155719
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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CO_1905645771593677618868059
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_1070610113163720804228423
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_1055731924224023963324305
null
[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_11_0" ]
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2023-12-01T23:00:32
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CO_1197389740182350912626276
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T14:42:57
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PO_5722842287632023142096424
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MD_9402372724898076044637979
null
[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_3_12" ]
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2023-12-01T23:00:32
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CO_8829353826904560924401950
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr32
Zr
A
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MD_1213582242930949697188121
2024-08-16T15:20:27
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PO_5978986357076713415474086
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MD_6922568494354637749731581
null
[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_4_15" ]
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2023-12-01T23:00:32
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CO_2992357500548763533722570
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr32
Zr
A
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CO_4544192507189510152781568
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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CO_2853778133791718273918512
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr17
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MD_1213582242930949697188121
2024-08-16T14:15:24
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PO_8808745683564111731511563
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_2518586880990335590339423
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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1
VASP
DFT-PBE
null
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null
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true
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{"input": {"ALGO": "fast", "EDIFF": "1E-8", "ENCUT": "400", "IBRION": "0", "ICHARG": "0", "ISIF": "2", "ISMEAR": "1", "ISTART": "0", "ISYM": "0", "KBLOCK": "10", "KGAMMA": "F", "KPAR": "16", "KSPACING": "0.24", "LCHARG": "T", "LREAL": "F", "LWAVE": "F", "MAXMIX": "50", "NBLOCK": "1", "NELM": "200", "NELMIN": "4", "NPAR": "8", "POTIM": "2", "PREC": "A", "PSTRESS": "0", "SIGMA": "0.15", "SMASS": "-1", "file-type": "INCAR"}, "hash": "12135822429309496971881212100548754870478961791137930949625877367285087883313386750731592539663054471050405358418449513543996992751906584969573924479043013", "id": "MD_1213582242930949697188121"}
MD_1213582242930949697188121
2024-08-16T15:15:00
3981395775539570212626141985813346065757563895760154486704162753119556853299229098235672186309939157993507385780901838624163474315544608028689335908564576
PO_3981395775539570212626141
{"materials-project-id": "mp-8635", "hash": "6922568494354637749731581470953761313340227251007968132409271298971738123971635607980429761926291238531556788585504056995350153047893169587863587413924336", "id": "MD_6922568494354637749731581"}
MD_6922568494354637749731581
null
[ "Zr_iter0_T1300_2_mp-8635_elastic_B222_dist03_3_1" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_1268828733404757434571697
23-Single-Element-DNPs_RSCDD_2023-Zr
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Zr" ]
1
4,730
4,730
81,165
0
4,730
0
4,730
0
4,730
-129.536477
10,022.893592
0
2023-12-01T18:03:07
[ [ 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/efb626b6
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0