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

Dataset card Data Studio Files Community
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:52:29
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:02:26
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null
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2023-12-01T22:52:29
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:35:12
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MD_8167787933279587874418320
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2023-12-01T22:52:29
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CO_4207535195206113048285440
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:40:03
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MD_8167787933279587874418320
null
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2023-12-01T22:52:29
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CO_7125019088636434283653276
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:25:24
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MD_8167787933279587874418320
null
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2023-12-01T22:52:29
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CO_3996246211353474963442605
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:04:41
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null
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2023-12-01T22:52:29
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CO_5001287999605122137782394
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:33:23
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PO_3508189185142812101719531
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MD_8167787933279587874418320
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2023-12-01T22:52:29
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CO_1142129355512624975817370
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al33
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MD_1213582242930949697188121
2024-08-16T15:12:49
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2023-12-01T22:52:29
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CO_6934331700141428264077864
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
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MD_1213582242930949697188121
2024-08-16T14:17:08
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PO_1535642738747567251853520
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T240_2_mp-998860_elastic_6" ]
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2023-12-01T22:52:29
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CO_1114181059761909583787963
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
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MD_1213582242930949697188121
2024-08-16T14:24:13
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PO_1014385221543829689781311
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_3" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_2776262888939130743758267
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:11:49
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_7692081366109509764469504
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:24:14
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PO_5542410356813891455481967
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_8723282683380866342987186
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:46:54
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PO_1102833967365538649962152
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_vacancies_18", "Al_iter_all_Al_iter0_T240_8_mp-1239196_vacancies_4" ]
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2023-12-01T22:52:29
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CO_7619774625367667194848538
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:22:53
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PO_8378974947406920250771504
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MD_9300119296539735821808460
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[ "Al_iter_all_Al_iter0_T960_0_mp-134_vacancies_Vac_0_19" ]
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2023-12-01T22:52:29
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CO_9881023397698149997516987
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:51:24
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_3661757869289322422132414
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:16:52
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2023-12-01T22:52:29
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CO_2285153406785442422128611
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:53:31
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CO_1303845055641197610809868
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:52:35
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PO_8630369445639993017825443
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2023-12-01T22:52:29
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CO_1371103339908235919675294
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:03:52
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_9" ]
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2023-12-01T22:52:29
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CO_1123468145006755985916450
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al33
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MD_1213582242930949697188121
2024-08-16T14:33:35
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_crowdion_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1010309897977397616733953
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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MD_1213582242930949697188121
2024-08-16T14:46:39
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PO_2464102986883682343044023
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_8" ]
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2023-12-01T22:52:29
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CO_1148731577724151195896248
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
A
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MD_1213582242930949697188121
2024-08-16T15:41:44
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null
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2023-12-01T22:52:29
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CO_8820424913237925366846701
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:10:29
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PO_4993084623133347215367971
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[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_6", "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_13" ]
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2023-12-01T22:52:29
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CO_5641606160484517351649183
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:34:23
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PO_1081615384992742044776221
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_17" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_7523546387356075792558087
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
A
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MD_1213582242930949697188121
2024-08-16T15:08:14
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_8", "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_19" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1198218337834519890744589
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:37:47
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PO_6489156007280430136402115
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_1096196860547867249057655
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:22:33
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MD_8167787933279587874418320
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2023-12-01T22:52:29
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CO_9419763450221345465946867
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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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
2024-08-16T15:06:07
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PO_3159709417353976808306589
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_15" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_2385202821618120402806793
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
1
2,572
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88,139
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-97.865127
3,139.699139
0
2023-12-01T17:52:38
[ [ 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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
Al
A
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1
VASP
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MD_1213582242930949697188121
2024-08-16T14:33:42
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_12" ]
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2023-12-01T22:52:29
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CO_1078105412712472295973241
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:22:07
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_5" ]
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2023-12-01T22:52:29
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CO_4441846361567777722767038
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
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MD_1213582242930949697188121
2024-08-16T14:17:14
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PO_6061366186994060035197686
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_17" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_2145696695050949719187997
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2023-12-01T17:52:38
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
A
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MD_1213582242930949697188121
2024-08-16T14:48:29
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_9" ]
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2023-12-01T22:52:29
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CO_5062276781714050945075192
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
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MD_1213582242930949697188121
2024-08-16T15:26:11
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_4601943793863614926407522
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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MD_1213582242930949697188121
2024-08-16T15:15:10
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MD_8167787933279587874418320
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2023-12-01T22:52:29
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CO_3695966897330905418660690
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al7
Al
A
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MD_1213582242930949697188121
2024-08-16T15:11:05
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[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_vacancies_13" ]
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2023-12-01T22:52:29
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CO_4037161252720452497334835
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:31:20
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MD_9300119296539735821808460
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2023-12-01T22:52:29
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CO_5986538443175950938096201
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:45:10
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2023-12-01T22:52:29
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CO_8400631180807829773175004
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:55:02
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2023-12-01T22:52:29
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:08:37
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MD_9300119296539735821808460
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2023-12-01T22:52:29
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CO_3018381065309130801203074
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T14:54:02
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_3" ]
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2023-12-01T22:52:29
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CO_2115056731698417698314826
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:27:29
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_vacancies_11" ]
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2023-12-01T22:52:29
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CO_3985615210029636714987767
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:26:41
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2023-12-01T22:52:29
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CO_4070742385729960990714802
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_db100_11" ]
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2023-12-01T22:52:29
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CO_5542630837222165810933461
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:33:06
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MD_9300119296539735821808460
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2023-12-01T22:52:29
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CO_9701784541141189440621656
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:53:58
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2023-12-01T22:52:29
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CO_1994363329401739199273171
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:52:29
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:30:26
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2023-12-01T22:52:29
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CO_6435672133045443050389618
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:59:20
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2023-12-01T22:52:29
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CO_2863670216969614128167207
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T15:23:34
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:33:48
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2023-12-01T22:52:29
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CO_1211473213547166774968840
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:46:34
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MD_9300119296539735821808460
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[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_10", "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_11" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_8877548919822278075324433
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:35:21
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MD_8342077683094605614607324
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[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_16" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1119732236866710419734069
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:21:25
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null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_0_2" ]
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2023-12-01T22:52:29
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CO_8369000712517606406684349
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:39:41
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PO_1690729891888980198306193
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_8" ]
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2023-12-01T22:52:29
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CO_8465056118228228563433102
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:30:07
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MD_8167787933279587874418320
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2023-12-01T22:52:29
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CO_1214095783953734728839096
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
A
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[ "Al" ]
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VASP
DFT-PBE
null
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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
2024-08-16T14:45:46
7831363393896791893918979455637227747956568496865586739706528597597737769636442601121154563848058257311889040151224079886713356978819457476704673133910708
PO_7831363393896791893918979
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_6", "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_10" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_9523356168264702066577423
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
1
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88,139
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2,572
-97.865127
3,139.699139
0
2023-12-01T17:52:38
[ [ 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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
Al
A
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[ "Al" ]
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MD_1213582242930949697188121
2024-08-16T14:14:50
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PO_1326518172449582500078047
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_12" ]
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2023-12-01T22:52:29
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CO_1286435192795111304803141
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:34:22
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PO_3807817075067618279505832
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_6734694548169160267810268
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
Al
A
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MD_1213582242930949697188121
2024-08-16T15:11:08
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PO_1102338206018450496745769
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_12" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_5257649451163352125385473
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2023-12-01T17:52:38
[ [ 1, 1, 1 ] ]
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2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
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MD_1213582242930949697188121
2024-08-16T15:15:12
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_2_5" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_6108223431424135605927396
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:42:09
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_14" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_3749073068659315429639222
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
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MD_1213582242930949697188121
2024-08-16T14:37:04
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PO_1321565517733012728905627
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_0_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_3922668014956311963295599
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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MD_1213582242930949697188121
2024-08-16T15:26:23
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter1_1_mp-1183144_elastic_B222_dist03_0_0" ]
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2023-12-01T22:52:29
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CO_3701251306751629794180694
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
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MD_1213582242930949697188121
2024-08-16T15:33:12
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PO_1058496177942639823891264
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T960_2_mp-998860_elastic_16" ]
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2023-12-01T22:52:29
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CO_2456361641307362542511770
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:14:51
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PO_8527190265795036967913753
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_0_1" ]
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2023-12-01T22:52:29
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CO_5160264721835685486278558
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
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MD_1213582242930949697188121
2024-08-16T15:23:53
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PO_1651236558251727423061470
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T240_2_mp-998860_elastic_11" ]
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2023-12-01T22:52:29
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CO_6704010682248608994681340
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
A
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MD_1213582242930949697188121
2024-08-16T14:18:33
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PO_8705150258808037076000558
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_3_1" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_4712515731959334491161060
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al33
Al
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MD_1213582242930949697188121
2024-08-16T14:13:35
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2023-12-01T22:52:29
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CO_2922356633140879773133597
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:20:07
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2023-12-01T22:52:29
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CO_1230878258270264286937874
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T14:47:48
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[ "Al_iter_all_Al_iter1_1_mp-1183144_elastic_B222_dist03_2_6" ]
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2023-12-01T22:52:29
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CO_1220793458840271009235326
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:53:57
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MD_8342077683094605614607324
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[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_14" ]
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2023-12-01T22:52:29
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CO_1289099351358103995828187
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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2024-08-16T14:19:32
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:19:47
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2023-12-01T22:52:29
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CO_6034436138313078863023182
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:59:20
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2023-12-01T22:52:29
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:15:55
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2023-12-01T22:52:29
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CO_1098674191205777027077162
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T14:20:00
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PO_4127906148903157877154817
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_8_4" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1277808813839630799040480
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
1
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2,572
-97.865127
3,139.699139
0
2023-12-01T17:52:38
[ [ 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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
Al
A
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[ "Al" ]
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1
VASP
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MD_1213582242930949697188121
2024-08-16T14:32:26
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_6" ]
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2023-12-01T22:52:29
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CO_9263213856080077227760249
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:51:34
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PO_4216803663411162609271759
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_9" ]
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2023-12-01T22:52:29
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CO_1287926556873421214222547
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
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2024-08-16T15:19:13
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CO_7205924293341151908786805
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:32:44
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2023-12-01T22:52:29
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CO_7384872285237204384218504
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:37:01
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PO_5948106556557165058190378
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_16" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1855706489152442176287833
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
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MD_1213582242930949697188121
2024-08-16T15:11:49
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PO_7694188352240081135969164
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_17" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_4078172642949018951903611
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al31
Al
A
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_1819823252769748730871040
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1092689733835166895275909
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CO_1583431517824865428102019
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:26:26
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PO_1112384675534191128226456
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_9" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_2684062948804164783721559
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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MD_1213582242930949697188121
2024-08-16T15:35:53
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter1_1_mp-1183144_elastic_B222_dist03_3_4" ]
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2023-12-01T22:52:29
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CO_5451038037452434351250495
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
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MD_1213582242930949697188121
2024-08-16T14:37:00
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PO_1133007120974483347209671
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_1291438743166332494365470
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:07:02
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PO_7834005054510912917505268
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_4" ]
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2023-12-01T22:52:29
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CO_2723847988589918291695027
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:18:17
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PO_2377871877753410911433986
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_1219258971391634494990743
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
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MD_1213582242930949697188121
2024-08-16T15:14:57
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PO_7081846188976454851766625
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T240_2_mp-998860_elastic_16" ]
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2023-12-01T22:52:29
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CO_1087615258013035892464194
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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CO_4355399530140276896837964
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
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MD_1213582242930949697188121
2024-08-16T14:30:29
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PO_8162435732450823295793397
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T960_2_mp-998860_elastic_13" ]
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2023-12-01T22:52:29
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CO_7278360892788363032038604
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
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MD_1213582242930949697188121
2024-08-16T14:50:04
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PO_3962275133850327569669329
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MD_8342077683094605614607324
null
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2023-12-01T22:52:29
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CO_5711694247330569566027231
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:22:53
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PO_6847010455587457023679652
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_18" ]
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2023-12-01T22:52:29
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CO_6501622196731458565723148
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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DFT-PBE
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null
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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
2024-08-16T14:48:15
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PO_1633010260475723017388658
{"materials-project-id": "mp-1183144", "hash": "8167787933279587874418320951248853394529876322379631497014846963005580728043288190655402346311637680323071163455556661885593388103969124639969091566467938", "id": "MD_8167787933279587874418320"}
MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter1_1_mp-1183144_elastic_B222_dist03_5_6" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1039038956337172216233262
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
1
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2,572
-97.865127
3,139.699139
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2023-12-01T17:52:38
[ [ 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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0