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

Dataset card Data Studio Files
xet
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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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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_iter1_0_mp-49_interstitials_HCP2_interOhB_1", "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interOhB_15", "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_interOhB_17", "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_interOhB_0" ]
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CO_7093565611041116620155730
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_1213582242930949697188121
2024-08-16T14:25:29
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PO_9366879902750449256114169
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[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_interOhB_1", "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interOhB_15", "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_interOhB_17", "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_interOhB_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7093565611041116620155730
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
2024-08-16T15:06:18
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MD_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7117151788505107770689645
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
2024-08-16T15:26:00
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_crowdion_825_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7119035861857903575655948
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
2024-08-16T14:46:38
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_3_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7122639475564923423928473
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
2024-08-16T15:37:59
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_10_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7142177088146808687560080
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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2024-08-16T14:50:48
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_1_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7154349623610127563539362
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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2024-08-16T15:15:48
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_6_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7162513931910470805172800
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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MD_1213582242930949697188121
2024-08-16T14:52:59
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2023-12-01T22:55:38
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CO_7178962289487470366013012
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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2023-12-01T22:55:38
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CO_7182773522541452255353426
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
Os16
Os
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2024-08-16T14:23:43
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MD_3410785766819930157739133
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2023-12-01T22:55:38
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CO_7191749068490584375330415
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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2024-08-16T14:22:03
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_7_9" ]
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2023-12-01T22:55:38
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CO_7200870101702382422889161
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
2024-08-16T14:56:45
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_2_8" ]
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2023-12-01T22:55:38
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CO_7208076417896609759196470
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
Os
Os
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MD_1213582242930949697188121
2024-08-16T14:40:41
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter2_1_mp-8643_7" ]
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2023-12-01T22:55:38
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CO_7222087323923215449949861
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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[ [ 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
Os8
Os
A
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VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:32:08
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MD_4076060147778651875063260
null
[ "Os_iter_all_Os_iter1_2_mp-1080694_6" ]
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2023-12-01T22:55:38
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CO_7223389526564997713462922
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
2024-08-16T15:24:00
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PO_8845703119644914213463309
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdionP_14" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7224479684504719015469581
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 ] ]
[ 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
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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
2024-08-16T14:55:03
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MD_1128333416791028182801865
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2023-12-01T22:55:38
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CO_7226195953350263057009471
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
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_4_2" ]
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2023-12-01T22:55:38
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CO_7232144073717667030409908
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
2024-08-16T14:25:34
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PO_7672956166177965673006898
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_interOhB_1" ]
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2023-12-01T22:55:38
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CO_7232871794150128379886859
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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2024-08-16T15:23:32
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdion_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7243372604743144320722081
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
2024-08-16T14:54:58
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[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_10_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7246337277295090384746460
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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Os
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2024-08-16T15:23:38
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null
[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_vacancies_Vac_0_15" ]
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2023-12-01T22:55:38
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CO_7247882161768844193766968
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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Os
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MD_1213582242930949697188121
2024-08-16T15:11:05
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MD_4076060147778651875063260
null
[ "Os_iter_all_Os_iter2_2_mp-1080694_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7262299781094635057169520
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
2024-08-16T14:54:58
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_0_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7282651837254755320325546
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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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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null
[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_7_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7285037995252408017771574
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
2024-08-16T14:46:53
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_9_15" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7289981806108394769923543
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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CO_7310314700334215581402499
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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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_3410785766819930157739133
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[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_11_12" ]
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2023-12-01T22:55:38
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CO_7353757235357117984515070
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
2024-08-16T15:01:43
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PO_1356422153977305451991580
{"materials-project-id": "mp-8643", "temperature": 3300, "hash": "11505114072996999782522726332492732342689169338055274625015282316729386836890269368660842133767952994883662910970674318543591055794857653122090907000376936", "id": "MD_1150511407299699978252272"}
MD_1150511407299699978252272
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_0_3300_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7371031325674916336283933
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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MD_1213582242930949697188121
2024-08-16T14:43:47
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter1_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_11_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7384858135072677277915105
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}
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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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2024-08-16T14:59:03
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_dbB_825_7" ]
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2023-12-01T22:55:38
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CO_7392835457190442767191286
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
2024-08-16T15:32:45
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MD_1086845055867124744315202
null
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2023-12-01T22:55:38
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CO_7395436840830154064958312
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
2024-08-16T14:41:55
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PO_2904323187163492798740260
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdionP_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7424578807741652679739059
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
A
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2024-08-16T14:42:50
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_6_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7435267771307416961359745
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
2024-08-16T14:21:21
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[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_10_15" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7443677529186436843855760
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_7498145982306146550950611
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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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_7519998082415012065047379
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
2024-08-16T14:40:34
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_4_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7520011869543843347924422
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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2024-08-16T15:35:20
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MD_1086845055867124744315202
null
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7527989696536913363111222
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
A
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MD_1213582242930949697188121
2024-08-16T14:56:45
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_7531051879829004751613173
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
2024-08-16T15:38:12
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_dbP_8" ]
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2023-12-01T22:55:38
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CO_7539838947825043607210182
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
A
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MD_1213582242930949697188121
2024-08-16T14:18:53
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PO_6516515716111253124035969
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_3_2" ]
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2023-12-01T22:55:38
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CO_7549598175157389685794380
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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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
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MD_1213582242930949697188121
2024-08-16T14:28:26
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MD_7572472347497086905713556
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[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_0_825_0" ]
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2023-12-01T22:55:38
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CO_7581343081980793109602610
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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2024-08-16T14:23:27
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CO_7586206329234133335981059
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
2024-08-16T15:21:42
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null
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2023-12-01T22:55:38
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CO_7594856484546566776069634
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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2024-08-16T14:53:28
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_3_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7611589994206287606582380
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
Os16
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MD_1213582242930949697188121
2024-08-16T14:51:20
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PO_2518997329123054099111653
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_8_19" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7621592176630204869784013
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
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MD_1213582242930949697188121
2024-08-16T14:22:55
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PO_5159831479292974845814509
{"materials-project-id": "mp-8643", "temperature": 3300, "hash": "11505114072996999782522726332492732342689169338055274625015282316729386836890269368660842133767952994883662910970674318543591055794857653122090907000376936", "id": "MD_1150511407299699978252272"}
MD_1150511407299699978252272
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_7_3300_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7629939981489673951423142
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
2024-08-16T15:02:33
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MD_1128333416791028182801865
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2023-12-01T22:55:38
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CO_7631296670143862151705073
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
2024-08-16T15:10:13
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_interTdB_3" ]
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2023-12-01T22:55:38
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CO_7648486575600171197895049
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
2024-08-16T14:57:58
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PO_8283683139576105140904529
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_crowdion_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7650664311195953065198173
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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[ [ 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
Os31
Os
A
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MD_1213582242930949697188121
2024-08-16T14:26:51
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2023-12-01T22:55:38
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CO_7668112190219344079048582
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
2024-08-16T15:34:28
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_dbP2_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7679713237430429529888388
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
Os31
Os
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7695740998126516668749999
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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2024-08-16T15:41:57
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7707791716994700884454415
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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2023-12-01T22:55:38
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CO_7716352412197175975358028
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
2024-08-16T15:32:06
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdionB_12" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7720501430435120924915125
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
2024-08-16T14:42:19
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_10_19" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7738623853174344861055145
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_7741609359240203077040923
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
Os16
Os
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MD_1213582242930949697188121
2024-08-16T14:23:11
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_7742800884742981477527692
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
2024-08-16T15:15:05
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MD_1118551595725510582628862
null
[ "Os_iter_all_Os_iter3_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_3300_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7743584098834624391491040
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
2024-08-16T15:38:08
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_8_17" ]
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2023-12-01T22:55:38
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CO_7753186136170695454766776
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
2024-08-16T14:40:59
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PO_1212057597214992286416357
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interOhB_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7754195966562519319255243
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_1213582242930949697188121
2024-08-16T15:19:12
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_0_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7760975743410040626047250
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
2024-08-16T14:44:59
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7767689259203339133385535
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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2024-08-16T14:22:05
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null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_interOh_9" ]
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2023-12-01T22:55:38
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CO_7779936779302425387018582
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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2024-08-16T14:24:01
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7783149733947322986437306
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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2024-08-16T14:23:25
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_2_10" ]
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2023-12-01T22:55:38
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CO_7786989931707159432836285
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
2024-08-16T14:46:04
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_7790183238318645271627351
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
2024-08-16T15:23:14
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_dbP2_6" ]
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2023-12-01T22:55:38
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CO_7790945063228816575690152
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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MD_1213582242930949697188121
2024-08-16T14:25:21
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PO_1202180158571198132278452
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_3_3300_16" ]
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2023-12-01T22:55:38
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CO_7792013806508485748968625
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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MD_3410785766819930157739133
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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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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_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_7819660718306821655352680
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_iter3_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_5_825_3" ]
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2023-12-01T22:55:38
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CO_7820769510883104199889309
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
2024-08-16T15:32:22
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_interOh_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7821700920167107540153620
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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MD_1213582242930949697188121
2024-08-16T15:10:36
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PO_5078361522367964558732895
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_0_7" ]
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2023-12-01T22:55:38
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CO_7828003874026818501738866
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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2024-08-16T14:24:49
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[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_4_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7842712223500629526861747
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
2024-08-16T14:27:29
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_3_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7863115159772089910472359
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
2024-08-16T14:27:22
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[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_2_3300_1" ]
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2023-12-01T22:55:38
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CO_7878533470227768963833435
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
2024-08-16T14:52:46
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interTd_0" ]
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2023-12-01T22:55:38
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CO_7891152766602828940885699
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
2024-08-16T15:24:40
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PO_6387256281677281952158723
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_dbB_825_6" ]
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2023-12-01T22:55:38
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CO_7894593739079737963817468
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
2024-08-16T15:36:08
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_7_14" ]
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2023-12-01T22:55:38
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CO_7899990710589574937887455
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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MD_1213582242930949697188121
2024-08-16T15:09:12
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2023-12-01T22:55:38
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CO_7902669667560175178383969
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
2024-08-16T15:18:44
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PO_1174739660807701183832008
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_2_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7913207700062896492205528
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
2024-08-16T14:46:38
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PO_1062143147621535042529576
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_4_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7916476013464787863171920
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
2024-08-16T14:54:53
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PO_3093420860873581953389496
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_10_3300_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7937906744016226387124742
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
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T15:27:57
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_10_0" ]
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2023-12-01T22:55:38
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CO_7946437054773005021988541
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_1213582242930949697188121
2024-08-16T14:42:55
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2023-12-01T22:55:38
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CO_7947455930116620328998595
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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2024-08-16T14:56:10
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_8_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7964445449160797718336239
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
2024-08-16T14:26:38
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_5_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7966853213227833750255161
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
2024-08-16T15:25:13
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PO_6363658174163446778714782
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_4_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7979168133515981401019757
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
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:34:43
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{"materials-project-id": "mp-49", "temperature": 3300, "hash": "805940665600861891488298321962321251903736026783089670253157528246044572519774039163404216522479752631494737067578798646377092638751844688917463099027558", "id": "MD_8059406656008618914882983"}
MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_db_3300_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7991489977840702603147234
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
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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
Os3
Os
A
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[ "Os" ]
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1
VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T14:59:29
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter1_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7992301944991359974926049
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 ] ]
[ 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
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
[ 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76 ]
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1
VASP
DFT-PBE
null
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{"input": {"ALGO": "fast", "EDIFF": "1E-8", "ENCUT": "400", "IBRION": "0", "ICHARG": "0", "ISIF": "2", "ISMEAR": "1", "ISTART": "0", "ISYM": "0", "KBLOCK": "10", "KGAMMA": "F", "KPAR": "16", "KSPACING": "0.24", "LCHARG": "T", "LREAL": "F", "LWAVE": "F", "MAXMIX": "50", "NBLOCK": "1", "NELM": "200", "NELMIN": "4", "NPAR": "8", "POTIM": "2", "PREC": "A", "PSTRESS": "0", "SIGMA": "0.15", "SMASS": "-1", "file-type": "INCAR"}, "hash": "12135822429309496971881212100548754870478961791137930949625877367285087883313386750731592539663054471050405358418449513543996992751906584969573924479043013", "id": "MD_1213582242930949697188121"}
MD_1213582242930949697188121
2024-08-16T14:24:18
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PO_9205403833182125478483123
{"materials-project-id": "mp-49", "hash": "3410785766819930157739133602960296775422439544612365590214994635763169177363191627840577432795366525135535563843886558553779195323694767533261615769563450", "id": "MD_3410785766819930157739133"}
MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_interTd_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
7994996766427436118093453948917519405976930352748098129309841050759751600454622946026843777795171413869618220081510354503517688783334482150542115937827468
CO_7994996766427436118093453
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
4,779
4,779
117,968
0
4,779
0
4,779
0
4,779
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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
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0