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

Dataset card Data Studio Files
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2024-08-16T14:17:20
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2023-12-01T22:55:38
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CO_5976144211584695982538306
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:55:38
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CO_5999483238215438241642318
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:21:11
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PO_4071986410001341490723647
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_6_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6012308656697681645760796
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:19:48
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PO_3196425101227521158245242
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_6_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6015181850574444653208222
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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2024-08-16T14:51:58
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6016101823492830010905368
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:19:25
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_6_6" ]
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2023-12-01T22:55:38
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CO_6048397929224016777206277
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:00:35
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PO_3266100012121543813032675
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_0_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6071596657021104630692490
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:42:48
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MD_1086845055867124744315202
null
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6082172636048700097523119
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:54:33
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MD_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6084003950640200939001616
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:34:54
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter1_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_9_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6087118048045343554131169
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:34:29
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PO_4197303174263752877197319
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_4_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6099692595862325508978508
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
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2023-12-01T17:56:11
[ [ 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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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CO_6100633821889909813057271
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:08:10
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_6108715301979248840360313
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2023-12-01T22:55:38
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CO_6115074057429181001389422
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:39:20
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2023-12-01T22:55:38
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CO_6172524834987920913765549
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:55:38
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23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:25:12
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_6_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6199213354002428962958611
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:39:51
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PO_7299834642320482073656750
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_interTdB_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6204125363000075091774258
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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MD_1213582242930949697188121
2024-08-16T15:39:13
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_9_9" ]
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2023-12-01T22:55:38
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CO_6210010255737574470409628
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:19:34
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PO_1066013660680117665157140
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MD_4076060147778651875063260
null
[ "Os_iter_all_Os_iter1_2_mp-1080694_vacancies_Vac_0_2" ]
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2023-12-01T22:55:38
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CO_6219669114507195817038577
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:57:14
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PO_2371888585894116680868327
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_4_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6233053597179253990604905
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
[ 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76 ]
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23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:55:38
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CO_6243930366435566380829165
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:55:38
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CO_6249646851838314037660137
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T15:35:08
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_11_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6255718423098161840168662
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T14:41:38
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_6_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6258097786955910078104727
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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CO_6259788173273506742090044
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:24:04
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_dbP_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6264581859482612619972676
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_8_14" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6280372240014738288910263
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2024-08-16T14:40:31
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6281578358656446182302582
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:34:40
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_dbB_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6286964744624860968316460
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T14:25:22
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2023-12-01T22:55:38
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CO_6296750354147445503417628
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:37:02
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MD_1086845055867124744315202
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2023-12-01T22:55:38
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CO_6328229381193496848142449
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T14:44:12
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_3_14" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6355333792691480826813855
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:39:33
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PO_1584537329578024537814323
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_2_17" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6357426881844447547142534
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:44:19
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_11_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6377651015526333134193240
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
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2023-12-01T17:56:11
[ [ 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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os15
Os
A
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CO_6381934823351770021001699
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:36:45
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_6400476245948307646923906
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
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MD_1086845055867124744315202
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2023-12-01T22:55:38
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CO_6444554676232990676041523
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:38:23
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_12" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6456488667244446459329067
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:00:20
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PO_7640304073971996026843164
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_11_18" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6472164586734829603662922
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
[ [ 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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:22:25
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdionB_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6472972317444762437910534
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:24:22
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_4_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6503489481591043461031313
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:28:55
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_0_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6506184387467531882108304
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:25:48
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_9_4" ]
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2023-12-01T22:55:38
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CO_6506573052950811182023391
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:49:20
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2023-12-01T22:55:38
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CO_6522894863534143564278453
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:49:20
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MD_3410785766819930157739133
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[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_4_9", "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_4_13", "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_4_4", "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_4_12" ]
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2023-12-01T22:55:38
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CO_6522894863534143564278453
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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Os
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MD_1213582242930949697188121
2024-08-16T14:49:20
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2023-12-01T22:55:38
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CO_6522894863534143564278453
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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Os
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MD_1213582242930949697188121
2024-08-16T14:49:20
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[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_4_9", "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_4_13", "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_4_4", "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_4_12" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6522894863534143564278453
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
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MD_1213582242930949697188121
2024-08-16T15:21:58
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_6_8" ]
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2023-12-01T22:55:38
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CO_6529155300251489306098244
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:38:32
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdion_5" ]
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2023-12-01T22:55:38
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CO_6530991236682394658946469
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T15:12:54
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PO_9891897820692787422593560
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_8_4" ]
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2023-12-01T22:55:38
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CO_6532555435720773334633624
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:22:03
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PO_9843545669218345463309099
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MD_1303044916320138948604021
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_9_825_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6545240978597068097133704
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:01:09
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_7_17" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6546737163508548247209029
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
[ [ 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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:56:20
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[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_interOhB_3300_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6554112925807352936499202
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:18:58
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6556569678878500858000881
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2024-08-16T14:19:23
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[ "Os_iter_all_Os_iter1_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_8_7" ]
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CO_6564138233045261828454765
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:19:21
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null
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2023-12-01T22:55:38
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CO_6566118036018922725833625
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:58:46
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_6571789467228642087574898
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:46:28
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PO_7618720576592272173499129
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_dbPP_825_2" ]
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2023-12-01T22:55:38
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CO_6585989089379322110700512
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:01:04
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_10_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6615497566639948005010892
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:28:12
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_3_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6625644529640382779205059
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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MD_1213582242930949697188121
2024-08-16T15:03:07
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[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_9_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6644021887564873927830399
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:09:05
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MD_1150511407299699978252272
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[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_11_3300_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6658589237805460729661540
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:55:38
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CO_6699370902214369400790752
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
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MD_7572472347497086905713556
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2023-12-01T22:55:38
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CO_6735761405663142267624042
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:02:37
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_10_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6756329826681458965977309
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:16:03
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_opt_12" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6763460904355189138926705
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:19:18
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_9_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6778824409001262234410143
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
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MD_1213582242930949697188121
2024-08-16T15:13:51
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_2_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6786512085907863475574635
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:33:35
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_6_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6787347319858269764582914
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:07:31
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_5_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6800986061001346399973513
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T15:03:34
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CO_6812794361338306842448812
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:22:58
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_dbPP_11" ]
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2023-12-01T22:55:38
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CO_6821697243706172322611150
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:17:54
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PO_8241479308970243763051641
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_6_3300_2" ]
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2023-12-01T22:55:38
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CO_6824605329884336529682753
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:45:17
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_2_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6828014604761069658312205
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:28:02
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PO_5821776739137418324830715
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_7_17" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6837414659243492874208106
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T15:01:52
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_10_9" ]
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CO_6858745501089143091700586
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
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MD_1213582242930949697188121
2024-08-16T14:53:48
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_6860376892613592693415674
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:01:46
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PO_1829633045859979107794474
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_9_825_2" ]
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2023-12-01T22:55:38
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CO_6861898517568959754215883
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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[ "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_5_2" ]
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2023-12-01T22:55:38
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CO_6867211286075068285415701
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_6_16" ]
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2023-12-01T22:55:38
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CO_6869133245103385402534711
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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[ "Os_iter_all_Os_iter2_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_9_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6877624081107579343928039
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T15:32:56
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_interOhB_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6880031187190866879327417
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T15:15:18
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PO_4481579183587965203604051
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdionP_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6888748671468189182773042
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
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4,779
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2023-12-01T17:56:11
[ [ 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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os2
Os
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MD_1213582242930949697188121
2024-08-16T14:19:39
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_1", "Os_iter_all_Os_iter2_0_mp-49_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6894118838145660222454452
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
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[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os2
Os
A
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MD_1213582242930949697188121
2024-08-16T14:19:39
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PO_2826246086505295539719799
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_1", "Os_iter_all_Os_iter2_0_mp-49_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6894118838145660222454452
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:23:13
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PO_3317753859715671325856504
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_1_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6927253620200827698898306
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:18:58
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PO_7265312485933119605149526
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interOhB_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6944874077015601325979812
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:24:21
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_db_0" ]
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2023-12-01T22:55:38
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CO_6955364172857494934669333
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:10:51
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_8_5" ]
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2023-12-01T22:55:38
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CO_6968050347057990165711882
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
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MD_1213582242930949697188121
2024-08-16T15:09:09
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MD_1303044916320138948604021
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_0_825_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6968198302594454526885002
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:57:52
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_dbP_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6974702533604937759845729
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T15:10:02
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PO_6139385552235381084064599
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_4_15" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_6988171430377749036760131
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
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4,779
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16,885.52072
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2023-12-01T17:56:11
[ [ 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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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MD_1213582242930949697188121
2024-08-16T14:42:17
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CO_6989153860648778173111123
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:13:00
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MD_7572472347497086905713556
null
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2023-12-01T22:55:38
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CO_6990070915157153219817669
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os15
Os
A
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MD_1213582242930949697188121
2024-08-16T14:19:33
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PO_7780220503458140959719762
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_vacancies_Vac_0_0" ]
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2023-12-01T22:55:38
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CO_7002530330297847189167186
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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DFT-PBE
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[ [ 0.7190659642219543, 1.882444143295288, 0.24029062688350677 ], [ -0.46148017048835754, 2.5110394954681396, -0.6220690011978149 ], [ 0.06780380755662918, 1.087121605873108, 3.1978836059570312 ], [ 0.16477446258068085, 0.9798225164413452, 3.4117910861968994 ], [ -0.05645214021205902, 3.2731592655181885, -4.447805404663086 ], [ -0.2469259798526764, 2.356074094772339, -4.506131172180176 ], [ -0.8478854894638062, 2.3263139724731445, -0.5838501453399658 ], [ 0.569478452205658, 3.037976026535034, -0.8925809264183044 ], [ 0.9810556173324585, -2.181391954421997, 0.48572343587875366 ], [ 0.9244359135627747, -1.4472328424453735, 0.026279179379343987 ], [ 0.15088793635368347, -3.1732194423675537, 4.501967430114746 ], [ -0.47276580333709717, -3.290200710296631, 4.971709251403809 ], [ -0.04151346907019615, -1.3392932415008545, -3.5979971885681152 ], [ 0.26375770568847656, -1.2842096090316772, -3.472870349884033 ], [ -1.0282042026519775, -2.116223096847534, 0.8178465962409973 ], [ -0.6859913468360901, -2.6221988201141357, 0.4698682725429535 ] ]
null
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{"input": {"ALGO": "fast", "EDIFF": "1E-8", "ENCUT": "400", "IBRION": "0", "ICHARG": "0", "ISIF": "2", "ISMEAR": "1", "ISTART": "0", "ISYM": "0", "KBLOCK": "10", "KGAMMA": "F", "KPAR": "16", "KSPACING": "0.24", "LCHARG": "T", "LREAL": "F", "LWAVE": "F", "MAXMIX": "50", "NBLOCK": "1", "NELM": "200", "NELMIN": "4", "NPAR": "8", "POTIM": "2", "PREC": "A", "PSTRESS": "0", "SIGMA": "0.15", "SMASS": "-1", "file-type": "INCAR"}, "hash": "12135822429309496971881212100548754870478961791137930949625877367285087883313386750731592539663054471050405358418449513543996992751906584969573924479043013", "id": "MD_1213582242930949697188121"}
MD_1213582242930949697188121
2024-08-16T15:41:07
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PO_6169679480290879860223249
{"materials-project-id": "mp-49", "hash": "3410785766819930157739133602960296775422439544612365590214994635763169177363191627840577432795366525135535563843886558553779195323694767533261615769563450", "id": "MD_3410785766819930157739133"}
MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_8_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7020320150402402449563861
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
1
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117,968
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4,779
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4,779
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4,779
-207.800307
16,885.52072
0
2023-12-01T17:56:11
[ [ 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}
10.60732/1ec0df98
3310305333373179395184373908907465024750856728734418909662937810603785626298670891195529851311793949595060868418647898387050878085548765620035810912218936
DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0