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Zr17
Zr
A
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[ "Zr" ]
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MD_1213582242930949697188121
2024-08-16T15:06:53
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PO_6888451827663882911911343
{"materials-project-id": "mp-131", "hash": "10557319242240239633243052075157509552013768715293155287413313665243709901949932522557582446835036231123736140426577800868669611783334574683439255201297053", "id": "MD_1055731924224023963324305"}
MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_crowdionP_7" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_7725733481432365196406260
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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2023-12-01T18:03:07
[ [ 1, 1, 1 ] ]
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2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/efb626b6
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr96
Zr
A
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MD_2978268964833510307558018
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[ "Zr_iter0_T550_1_mp-1077723_elastic_B222_dist03_9_3" ]
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2023-12-01T23:00:32
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CO_7667356274135035400078285
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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Zr
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MD_1213582242930949697188121
2024-08-16T15:40:36
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PO_2301117600451717140012158
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MD_9402372724898076044637979
null
[ "Zr_iter2_4_mp-1056376_elastic_B222_dist03_2_5", "Zr_iter0_T1300_4_mp-1056376_elastic_B222_dist03_2_1" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:31
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CO_7580646918031283372588212
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_9739429181741294004829608
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
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2023-12-01T23:00:32
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CO_1273800104348650235680413
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
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MD_6922568494354637749731581
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2023-12-01T23:00:32
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CO_1035640342158991940165886
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
Zr16
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2024-08-16T14:41:20
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CO_1246491707015344594602147
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
2024-08-16T14:51:11
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PO_9878833963202006538573391
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MD_1242681989026378489058465
null
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2023-12-01T23:00:32
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CO_2364459689821048547673389
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
2024-08-16T15:39:47
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PO_1109440218885101534501030
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MD_1053968927990176692110395
null
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2023-12-01T23:00:32
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CO_2882589756561791933373999
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
2024-08-16T15:25:47
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_interTd_10" ]
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2023-12-01T23:00:32
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CO_9143635380222431018209265
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
2024-08-16T14:15:21
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MD_6368844128943499733756333
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2023-12-01T23:00:32
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CO_1085794847680883138305310
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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A
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MD_1213582242930949697188121
2024-08-16T14:20:20
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PO_7227769964012661997835736
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MD_9402372724898076044637979
null
[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_11_19" ]
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2023-12-01T23:00:32
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CO_2834197421056064989179226
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
2024-08-16T15:06:04
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PO_4416307903025779199600988
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MD_6368844128943499733756333
null
[ "Zr_iter3_2_mp-8635_vacancies_Vac_0_2200_8" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_2531748875229022615795790
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
Zr
A
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null
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MD_1213582242930949697188121
2024-08-16T14:54:55
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PO_9447029704103438454810582
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MD_9402372724898076044637979
null
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2023-12-01T23:00:32
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CO_9028008097293094698350653
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
A
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VASP
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null
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MD_1213582242930949697188121
2024-08-16T15:00:12
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PO_1040492429529865600635776
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MD_9402372724898076044637979
null
[ "Zr_iter0_T1300_4_mp-1056376_elastic_B222_dist03_0_2" ]
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2023-12-01T23:00:32
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CO_7451891244057516277893394
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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2023-12-01T18:03:07
[ [ 1, 1, 1 ] ]
[ 3 ]
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
Zr16
Zr
A
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MD_1213582242930949697188121
2024-08-16T14:48:39
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2023-12-01T23:00:32
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CO_8775587806944797085940505
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
2024-08-16T15:17:19
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2023-12-01T23:00:32
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CO_1019521825229118153006027
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_6001304011902645998602053
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
2024-08-16T15:37:37
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MD_1055731924224023963324305
null
[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_5_18" ]
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2023-12-01T23:00:32
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CO_6317324290744017434101443
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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MD_1213582242930949697188121
2024-08-16T15:31:26
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MD_9402372724898076044637979
null
[ "Zr_iter2_4_mp-1056376_1", "Zr_iter0_T1300_4_mp-1056376_2" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:31
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CO_6707757882175980082991231
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
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MD_1213582242930949697188121
2024-08-16T14:30:09
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PO_7010847507404950762370078
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MD_2794717748642297120678119
null
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2023-12-01T23:00:32
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CO_7968690191730414747173375
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
2024-08-16T14:30:12
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PO_2187523654580793552348454
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MD_2794717748642297120678119
null
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2023-12-01T23:00:32
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CO_8735442435920121846531421
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
[ 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
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MD_1213582242930949697188121
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MD_9402372724898076044637979
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CO_7652584186414492240724429
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
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MD_1213582242930949697188121
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CO_3260805527552938988236900
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
2024-08-16T15:07:05
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PO_8282607743516082399067873
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MD_1265425156488878603940539
null
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2023-12-01T23:00:32
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CO_1950718734221063580910829
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_9952992650583014356802983
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
2024-08-16T14:26:53
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MD_9402372724898076044637979
null
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2023-12-01T23:00:32
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CO_6842195036045985431188230
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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MD_1213582242930949697188121
2024-08-16T14:40:36
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MD_6922568494354637749731581
null
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CO_7044623756684377506861338
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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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
2024-08-16T14:20:33
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PO_9077447916057205578180150
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MD_9402372724898076044637979
null
[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_2_8" ]
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2023-12-01T23:00:32
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CO_2421703633893414325854608
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
[ 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}
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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
2024-08-16T15:00:49
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PO_3968076782321799363114027
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MD_9402372724898076044637979
null
[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_3_11" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_1047523386240624130728310
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, 1, 1 ] ]
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[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0