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

Dataset card Data Studio Files Community
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Zr16
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CO_4565005050631875216176336
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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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
2024-08-16T14:19:43
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PO_1129104318901323498134113
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MD_6368844128943499733756333
null
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2023-12-01T23:00:32
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CO_5434097367260363946448331
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
2024-08-16T15:38:11
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PO_2514440158144998521688046
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MD_5279706486609828620642959
null
[ "Zr_iter0_T2200_3_mp-41_elastic_B222_dist03_2_17" ]
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2023-12-01T23:00:32
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CO_6270668399755991927318185
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
A
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MD_1213582242930949697188121
2024-08-16T14:18:15
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PO_9370222974394951314692537
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MD_3162313128594702633754619
null
[ "Zr_iter3_3_mp-41_elastic_B222_dist03_2_2200_8" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_4306236981853689962983033
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
Zr
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MD_1213582242930949697188121
2024-08-16T14:42:36
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_crowdion_18" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_3238032224593414948246403
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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2023-12-01T18:03:07
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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
2024-08-16T14:25:18
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PO_2184693318002023013791231
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MD_5279706486609828620642959
null
[ "Zr_iter0_T550_3_mp-41_vacancies_Vac_0_110" ]
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2023-12-01T23:00:32
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CO_7549018908847666999588121
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
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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
2024-08-16T15:39:55
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PO_1225057063692679375966770
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MD_9402372724898076044637979
null
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2023-12-01T23:00:32
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CO_9505728162506037836174588
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
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CO_1218065301954334169292821
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
2024-08-16T14:13:57
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_1229325783740059590812458
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
2024-08-16T14:28:53
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PO_1320933654707975108514127
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MD_1242681989026378489058465
null
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2023-12-01T23:00:32
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CO_9186904563576257086647506
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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2024-08-16T14:23:37
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CO_7611172023012723774388676
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
Zr8
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MD_1213582242930949697188121
2024-08-16T14:35:49
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MD_9402372724898076044637979
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2023-12-01T23:00:32
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CO_1007706617870649227364714
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
2024-08-16T14:20:53
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MD_1055731924224023963324305
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2023-12-01T23:00:32
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CO_8658049914059080072563142
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
2024-08-16T14:38:16
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MD_9402372724898076044637979
null
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CO_9683592510333965324174486
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
2024-08-16T15:25:44
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PO_5720155946953740647176635
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MD_1274262212474641148263264
null
[ "Zr_iter3_1_mp-1077723_vacancies_Vac_0_2200_5" ]
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2023-12-01T23:00:32
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CO_1146006712599088069349410
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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2023-12-01T18:03:07
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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
2024-08-16T14:35:41
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PO_1127030969596491222118822
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MD_5279706486609828620642959
null
[ "Zr_iter0_T2200_3_mp-41_elastic_B222_dist03_9_11" ]
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2023-12-01T23:00:32
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CO_1487499738799173449247160
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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CO_9532765531328255679156136
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_4096450544866044101443446
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
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CO_3044265486297009239403672
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
2024-08-16T14:11:46
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MD_1055731924224023963324305
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CO_1160745418906942600694625
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
2024-08-16T15:34:51
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_3714137649810239643428045
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
2024-08-16T14:47:42
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MD_9402372724898076044637979
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2023-12-01T23:00:32
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CO_1101837986372570668133027
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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2024-08-16T14:39:32
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null
[ "Zr_iter0_T1300_2_mp-8635_elastic_B222_dist03_5_8" ]
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2023-12-01T23:00:31
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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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{'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
2024-08-16T14:51:42
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2023-12-01T23:00:32
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CO_1214625498727850103786581
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
2024-08-16T15:29:53
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null
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2023-12-01T23:00:32
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CO_1337217173203752575809481
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_1288633595833812749977994
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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2024-08-16T14:13:27
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CO_1120233072495709557654566
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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2024-08-16T14:21:16
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CO_8870354782160211798644467
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
2024-08-16T15:25:55
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[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_8_18" ]
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CO_1605012921928919340114408
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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2024-08-16T14:31:13
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null
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CO_1075387978175657116520871
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
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MD_1213582242930949697188121
2024-08-16T14:44:18
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PO_1282079013080140801735023
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MD_5279706486609828620642959
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2023-12-01T23:00:32
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CO_7005054090666762532398090
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
2024-08-16T14:52:03
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PO_3534992164632520712618703
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MD_6922568494354637749731581
null
[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_1_5" ]
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CO_2387929735441499623103258
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
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PO_1309223473245333756766403
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MD_1055731924224023963324305
null
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CO_3918470317251639519125158
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
2024-08-16T14:11:54
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2023-12-01T23:00:32
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CO_1175903275479827629452387
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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2024-08-16T15:19:12
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2023-12-01T23:00:32
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CO_1398264492782196939736127
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
2024-08-16T15:22:29
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2023-12-01T23:00:32
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CO_1190365392760493418371102
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
2024-08-16T14:14:59
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PO_6851496710396738392826963
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MD_3162313128594702633754619
null
[ "Zr_iter3_3_mp-41_elastic_B222_dist03_4_2200_4" ]
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2023-12-01T23:00:32
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CO_2551029587054294608155944
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_5735441759550932516660691
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
2024-08-16T14:18:21
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null
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2023-12-01T23:00:32
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CO_1239264229176387846528674
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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MD_1213582242930949697188121
2024-08-16T14:12:31
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PO_2347027922819577841975355
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MD_5279706486609828620642959
null
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CO_1028599838490835704872007
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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2024-08-16T14:44:54
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2023-12-01T23:00:32
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CO_2901640269828378320227118
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
2024-08-16T14:40:50
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2023-12-01T23:00:32
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CO_1160527828800472235176444
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
2024-08-16T14:57:22
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PO_1290647830340254691388411
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_1925397644733498570045608
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_1230921824351645777752764
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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null
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2023-12-01T23:00:32
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CO_1320005883557922876426260
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
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MD_1055731924224023963324305
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CO_1192101764817499656545299
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
2024-08-16T15:27:57
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MD_9402372724898076044637979
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2023-12-01T23:00:32
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CO_3881061775496705211636089
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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2024-08-16T14:42:28
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MD_1055731924224023963324305
null
[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_dbPP_11" ]
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CO_6958796382248225395775494
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_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_1178203521675099189884642
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
2024-08-16T14:32:15
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_1137012052083832583187549
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
2024-08-16T14:13:02
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MD_5279706486609828620642959
null
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CO_1110037224126707292392869
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
2024-08-16T15:03:46
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MD_5279706486609828620642959
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2023-12-01T23:00:32
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CO_1230222286264694663175409
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
2024-08-16T15:09:12
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PO_7313428867555773081852756
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_8369536156733721436583540
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
Zr16
Zr
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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
2024-08-16T15:29:33
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null
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2023-12-01T23:00:32
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CO_9998262533287537055296884
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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2024-08-16T14:25:06
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CO_5446116792373620979986234
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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2024-08-16T15:36:54
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CO_5771885810955887858842938
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
2024-08-16T14:21:02
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_7592694542859352885455174
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
2024-08-16T14:12:47
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_3371969405407977402899790
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
2024-08-16T14:38:24
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MD_1055731924224023963324305
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[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_interOh_2" ]
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CO_2016818188945285858449257
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_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_5788702581039421027605184
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
2024-08-16T14:20:25
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MD_9402372724898076044637979
null
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2023-12-01T23:00:32
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CO_8507882287070865550963618
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
2024-08-16T15:18:11
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MD_5279706486609828620642959
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2023-12-01T23:00:32
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CO_8990716979595576497526070
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
2024-08-16T15:12:28
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CO_6265749755450973065981218
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
2024-08-16T15:20:42
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MD_1055731924224023963324305
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2023-12-01T23:00:32
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CO_1158565680189400524601730
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
2024-08-16T14:15:19
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MD_6922568494354637749731581
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2023-12-01T23:00:31
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CO_1264115641649932263736183
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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[ "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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2024-08-16T14:30:57
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CO_9616651665684379992645808
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
2024-08-16T15:33:48
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2023-12-01T23:00:32
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CO_2595532292324192327864338
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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MD_1055731924224023963324305
null
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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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{'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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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_1210155095926852722732113
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
2024-08-16T15:12:26
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PO_1001616787615645216825000
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MD_1055731924224023963324305
null
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2023-12-01T23:00:32
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CO_4560934947908526091398839
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_1347110277421720844594685
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
2024-08-16T15:20:41
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PO_2412080964024583372519083
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MD_1265425156488878603940539
null
[ "Zr_iter3_0_mp-131_interstitials_HCP2_dbB_550_2" ]
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2023-12-01T23:00:32
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CO_1253055661670879627627067
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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2024-08-16T15:23:04
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MD_6922568494354637749731581
null
[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_10_10" ]
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2023-12-01T23:00:32
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CO_4495688386850922996986776
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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2024-08-16T15:39:59
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CO_8147057981153984181560683
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
2024-08-16T14:13:50
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CO_1216555295943982491369082
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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MD_1213582242930949697188121
2024-08-16T14:12:35
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MD_5279706486609828620642959
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2023-12-01T23:00:32
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CO_1202604841391823134825190
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
2024-08-16T15:03:45
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MD_1055731924224023963324305
null
[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_interTdB_6", "Zr_iter0_T1300_0_mp-131_interstitials_HCP2_interTdB_1", "Zr_iter2_0_mp-131_interstitials_HCP2_interTdB_2" ]
[ "DS_h9w8v7289utq_0" ]
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CO_1153920536340554881512155
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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2024-08-16T15:01:18
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MD_1053968927990176692110395
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[ "Zr_iter1_3_mp-41_550_4" ]
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2023-12-01T23:00:31
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CO_1339078403245791464806833
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
2024-08-16T14:46:52
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PO_1284977770529047321422989
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MD_5279706486609828620642959
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[ "Zr_iter0_T550_3_mp-41_vacancies_Vac_0_34" ]
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2023-12-01T23:00:32
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CO_6042333697747285156708522
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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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
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MD_1213582242930949697188121
2024-08-16T15:18:53
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PO_1380325352734762058649905
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MD_8829392809605781739714239
null
[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_8_2200_2" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
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CO_6929927523341217459925877
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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2024-08-16T14:21:06
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CO_5771839737078093273600921
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
2024-08-16T14:42:36
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2023-12-01T23:00:32
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CO_6634767177992271217682924
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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2024-08-16T15:23:53
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PO_2812079606523701035741964
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MD_1055731924224023963324305
null
[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_crowdionB_0" ]
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2023-12-01T23:00:32
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CO_9511221965725376457202138
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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VASP
DFT-PBE
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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
2024-08-16T14:49:56
1223546537377292010720588088035573580643807253238543154653060561308244655759773020520274138797907802476700590327701308353505512051826815830844031031251245
PO_1223546537377292010720588
{"materials-project-id": "mp-1077723", "hash": "2978268964833510307558018165451815669660862885093647563418774150216007238116466564434899240502680071669631246137311293660883876635781766541306709304579310", "id": "MD_2978268964833510307558018"}
MD_2978268964833510307558018
null
[ "Zr_iter0_T550_1_mp-1077723_elastic_B222_dist03_9_4" ]
[ "DS_h9w8v7289utq_0" ]
2023-12-01T23:00:32
12588711723895073024558977082492245884200076506208873047777655725472901999000480769544843038834198443768627885807294329123381925688721138919847522785628178
CO_1258871172389507302455897
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
3779166078439729169045676638687591248938741611506104834905939473860873638012917238708812386198413249272850425928198537990613089843430604960860386443114637
DS_h9w8v7289utq_0
23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0
Zr16
Zr
A
[ 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40 ]
[ "Zr" ]
[ 1 ]
1
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2023-12-01T23:00:31
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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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2024-08-16T15:15:34
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2023-12-01T23:00:32
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CO_6992208392654934190556772
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
2024-08-16T14:11:59
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2023-12-01T23:00:32
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CO_1168448057098965101172972
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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CO_5665314775251206642589778
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_1138795047249260574503052
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
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CO_3014726907465603098509982
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
2024-08-16T15:39:34
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[ "Zr_iter0_T1300_0_mp-131_interstitials_HCP2_dbP_15", "Zr_iter0_T1300_0_mp-131_interstitials_HCP2_dbP_21" ]
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CO_9504842444227989923330523
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
2024-08-16T15:03:21
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MD_5279706486609828620642959
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2023-12-01T23:00:32
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CO_2265320265772593704983017
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
2024-08-16T14:58:05
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PO_2670850889124551034964043
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MD_1053968927990176692110395
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2023-12-01T23:00:32
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CO_6315521652125649320418493
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_6368844128943499733756333
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2023-12-01T23:00:32
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CO_1014427177038995762144446
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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2024-08-16T15:36:13
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MD_6368844128943499733756333
null
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2023-12-01T23:00:32
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CO_5965804690627701228953756
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
2024-08-16T15:14:44
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PO_4715428548653435941962163
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MD_9402372724898076044637979
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CO_8850392582215440875153667
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