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

Dataset card Data Studio Files Community
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2024-08-16T14:16:00
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[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_0" ]
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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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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:18:33
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PO_1315814428532197159976559
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_1293565259959444559014524
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
A
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MD_1213582242930949697188121
2024-08-16T14:13:10
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PO_1080883559013948658741247
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_2_4" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1167350393225705009564196
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
Al
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2024-08-16T15:07:28
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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
2024-08-16T15:20:53
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null
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2023-12-01T22:52:29
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CO_8433343102266724610760170
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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2024-08-16T14:27:51
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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
2024-08-16T14:34:13
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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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2024-08-16T15:15:14
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2023-12-01T22:52:29
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CO_6926097942811599125688548
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
A
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MD_1213582242930949697188121
2024-08-16T14:28:37
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PO_3135966233213478873798275
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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_7265068144717972929693493
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}
10.60732/ef6f5966
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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
2024-08-16T14:14:03
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PO_1283254890642549866733682
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_vacancies_2" ]
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2023-12-01T22:52:29
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CO_1174840892232621753342727
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
2024-08-16T15:39:25
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PO_4660025647483206815319880
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T240_2_mp-998860_elastic_13" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_4294048055513649007425031
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
Al16
Al
A
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2024-08-16T15:08:03
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_7320528170340017157011239
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
2024-08-16T15:30:19
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_5068033793736974780157608
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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2024-08-16T15:38:55
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter1_0_mp-134_elastic_B222_dist03_5_7" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_4974828099567481420790703
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
2024-08-16T15:03:03
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PO_2970430659514053875557928
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_3208948227662795255181399
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
Al32
Al
A
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MD_1213582242930949697188121
2024-08-16T14:28:21
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PO_6732754641929804843171871
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_3584093330725092458378755
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
2024-08-16T14:43:59
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PO_5186506472300416220657765
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null
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2023-12-01T22:52:29
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CO_8975291902518683167576948
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
2024-08-16T15:15:37
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PO_2040085668151998810958861
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_1_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_3228494396070834304695406
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
2024-08-16T15:26:55
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PO_4227617663545115332646537
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_5" ]
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2023-12-01T22:52:29
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CO_1030134222852625446706757
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
2024-08-16T14:40:30
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PO_2478382251808891917658252
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_14" ]
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2023-12-01T22:52:29
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CO_5960971420040264492692356
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
A
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MD_1092689733835166895275909
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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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2024-08-16T14:40:51
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CO_8482618511337432503794284
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
2024-08-16T14:15:34
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_1328203874328252264129689
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
2024-08-16T14:43:49
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null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_interOh_2" ]
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2023-12-01T22:52:29
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CO_7801580656145370363261671
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
2024-08-16T15:16:47
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PO_2735049066367888632352219
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_1300665485433412376749719
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
Al16
Al
A
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2024-08-16T14:54:49
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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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2024-08-16T14:30:21
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2023-12-01T22:52:29
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CO_8325425946246693302020506
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
2024-08-16T15:05:44
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PO_8736163158584471247903124
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T960_2_mp-998860_elastic_5" ]
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2023-12-01T22:52:29
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CO_5230377859096409300010260
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
2024-08-16T14:35:27
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MD_8167787933279587874418320
null
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2023-12-01T22:52:29
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CO_1131216195263901399304455
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
2024-08-16T14:53:23
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_1", "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_13" ]
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2023-12-01T22:52:29
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CO_1098567255792942646303834
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
2024-08-16T15:19:41
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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
2024-08-16T15:37:59
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2023-12-01T22:52:29
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CO_4441937325203495744883185
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
2024-08-16T15:08:27
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PO_9168265401324589940727315
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_12" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_4747947150403491911337072
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
[ [ 1, 1, 1 ] ]
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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
Al64
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MD_1213582242930949697188121
2024-08-16T15:24:47
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2023-12-01T22:52:29
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CO_1051607797765902484615240
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
2024-08-16T14:37:35
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PO_9994209854251759811608393
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_1224014991391690674932882
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
2024-08-16T14:42:27
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2023-12-01T22:52:29
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CO_6506398768940814263831565
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
Al33
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MD_1213582242930949697188121
2024-08-16T14:16:08
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null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_18" ]
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2023-12-01T22:52:29
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CO_1241623756119992147227186
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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null
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MD_1213582242930949697188121
2024-08-16T15:17:45
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PO_3653724369330077727483928
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_6" ]
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2023-12-01T22:52:29
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CO_8688388258453166020696217
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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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
A
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MD_1213582242930949697188121
2024-08-16T14:58:13
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_0" ]
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2023-12-01T22:52:29
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CO_8951347609723182387379317
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
2024-08-16T15:16:04
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_8" ]
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2023-12-01T22:52:29
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CO_5708357454113485618792674
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
2024-08-16T15:25:39
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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_1179462980374911059538222
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
2024-08-16T15:36:20
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter1_0_mp-134_elastic_B222_dist03_2_4" ]
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2023-12-01T22:52:29
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CO_1192015220701073251341728
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
2024-08-16T15:38:04
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2023-12-01T22:52:29
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CO_9480034842297947395721008
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
2024-08-16T15:02:36
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2023-12-01T22:52:29
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CO_9864845542926997719508104
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
2024-08-16T14:52:51
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CO_6117662089798613154727414
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
2024-08-16T15:31:40
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_1100564652506864515180975
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
2024-08-16T14:40:31
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2023-12-01T22:52:29
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CO_3466237881364639246503705
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
2024-08-16T14:52:37
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PO_5184440080515045123181643
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MD_8167787933279587874418320
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2023-12-01T22:52:29
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CO_1084367709645214227431989
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
2024-08-16T14:30:46
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_1247993611166546262452271
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
2024-08-16T15:06:05
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MD_8167787933279587874418320
null
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2023-12-01T22:52:29
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CO_1265683333819279495971234
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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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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CO_1289314030989241509765765
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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2024-08-16T14:13:03
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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
2024-08-16T15:28:31
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2023-12-01T22:52:29
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CO_5576229335159815882175545
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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[ "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
2024-08-16T14:45:41
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2023-12-01T22:52:29
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CO_1847034040217851030533895
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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CO_1050177482707468067707666
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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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
Al33
Al
A
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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
2024-08-16T14:52:19
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PO_2556403414450682239832421
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_interOh_3" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_4313002720035825570544224
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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88,139
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2,572
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2,572
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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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MD_1213582242930949697188121
2024-08-16T14:45:36
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_2_7" ]
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2023-12-01T22:52:29
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CO_5455703832002799344158477
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
2024-08-16T14:18:30
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PO_5986565946886856701570927
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_2" ]
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2023-12-01T22:52:29
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CO_3227979481683888867439599
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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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
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MD_1213582242930949697188121
2024-08-16T15:05:28
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PO_1316009566270952176546770
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_2_3" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_5180958180853312867453686
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}
10.60732/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
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MD_1213582242930949697188121
2024-08-16T14:46:17
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_14" ]
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2023-12-01T22:52:29
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CO_9415428545390375667154559
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
2024-08-16T15:28:10
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter1_0_mp-134_interstitials_FCC2_interTd_4" ]
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2023-12-01T22:52:29
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CO_1043343290789115618613575
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
Al32
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MD_1213582242930949697188121
2024-08-16T15:09:36
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter1_0_mp-134_elastic_B222_dist03_4_7" ]
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2023-12-01T22:52:29
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CO_1257233034890869525140356
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
A
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MD_1213582242930949697188121
2024-08-16T14:35:33
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null
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2023-12-01T22:52:29
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CO_1087882988455880555337094
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
2024-08-16T14:14:37
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_1086905187068317462592380
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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23-Single-Element-DNPs_RSCDD_2023-Al
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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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2024-08-16T15:17:05
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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
[ "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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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2023-12-01T22:52:29
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CO_8317400579085739086795792
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
2024-08-16T15:14:32
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PO_5306143264282533415631705
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_9404773329849321411993928
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
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MD_1213582242930949697188121
2024-08-16T15:11:59
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PO_1009486286737654466167033
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_vacancies_8" ]
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2023-12-01T22:52:29
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CO_3481580598500238011825452
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
Al33
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MD_1213582242930949697188121
2024-08-16T15:15:29
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PO_9606919685810959954791414
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_db111_3", "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_db111_8" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_5481498650046382385280486
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 ] ]
[ 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}
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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
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MD_1213582242930949697188121
2024-08-16T15:16:35
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PO_4326748555287847389884911
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T960_2_mp-998860_elastic_8" ]
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2023-12-01T22:52:29
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CO_8644077386068136717153582
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
2024-08-16T15:06:33
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PO_8333743777860549523376493
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_7", "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_8" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_2776831417214849628921922
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
Al32
Al
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[ "Al_iter_all_Al_iter1_0_mp-134_elastic_B222_dist03_5_2", "Al_iter_all_Al_iter1_0_mp-134_elastic_B222_dist03_5_5" ]
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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
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2023-12-01T22:52:29
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CO_4460657255392831849082908
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
2024-08-16T15:04:03
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PO_4856732488534323143992148
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_6_1" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_7536513386043702131908574
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
Al32
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MD_1213582242930949697188121
2024-08-16T15:28:43
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PO_1322794376308949381264294
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_1" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1198667641379658091937463
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
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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
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[ "Al" ]
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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
2024-08-16T14:26:37
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PO_1310603122174238351542076
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_8" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_8904105272194084984130440
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 ] ]
[ 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
DFT-PBE
null
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null
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true
null
null
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10.30546
43.488454
{"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
2024-08-16T14:48:40
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PO_2477782897946434097011956
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_4" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_8704026435448028556890722
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
2,572
88,139
0
2,572
0
2,572
0
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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[ true, true, true ]
[ 1, 1, 1 ]
3
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1
VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T14:15:15
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PO_1015254495964500277558802
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_6_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1739345659258274543168725
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
2024-08-16T15:05:09
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_2" ]
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2023-12-01T22:52:29
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CO_7035871245368763646064665
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
2024-08-16T14:51:02
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PO_1569964856357248243724524
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_4" ]
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2023-12-01T22:52:29
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CO_1005605034304542295768731
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
Al16
Al
A
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MD_1213582242930949697188121
2024-08-16T14:12:21
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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_1055810212510154766705617
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
Al64
Al
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MD_1213582242930949697188121
2024-08-16T15:02:56
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PO_9567916097244570527048422
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_4" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_9741017533063662945627923
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
2024-08-16T14:35:22
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PO_1884420110191948206344058
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_7" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1295953633701381684835440
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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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
2024-08-16T15:30:59
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PO_9875743216898381619182121
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_9_8" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1624771082184318097737914
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
Al33
Al
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MD_1213582242930949697188121
2024-08-16T14:15:30
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PO_1428657035844577939142321
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_15" ]
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2023-12-01T22:52:29
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CO_1307221101504677206034461
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
2024-08-16T15:31:22
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PO_2776280550465550807111209
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_7" ]
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2023-12-01T22:52:29
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CO_1295390083050482586343181
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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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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2023-12-01T22:52:29
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CO_2666832815412813120964718
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
2024-08-16T14:29:26
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PO_3075567906983116396604958
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T240_2_mp-998860_elastic_14" ]
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2023-12-01T22:52:29
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CO_5113708513998578736112875
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
Al33
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MD_1213582242930949697188121
2024-08-16T14:27:27
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PO_7815058935487832838878519
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_5915939478221979203374665
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
Al32
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null
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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
2024-08-16T14:39:18
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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
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2023-12-01T22:52:29
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CO_2752893036531519951078544
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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