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

Dataset card Data Studio Files
xet
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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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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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MD_1213582242930949697188121
2024-08-16T14:22:08
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_9_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8039757517394562684524688
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:25:42
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PO_6144944935220781954318541
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_1_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8040842183180061721454642
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T15:34:38
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null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_2_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8041540324569657390074990
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
2024-08-16T15:24:50
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MD_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8049589133313056859507229
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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2024-08-16T14:29:30
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[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_7_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8051261316408626206314021
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
2024-08-16T15:12:16
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8062355503716411225345337
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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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8079752736504951622698850
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:01:06
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_5_825_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8098096527227634785531878
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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MD_1213582242930949697188121
2024-08-16T15:42:44
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_6_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8118161860476577769096323
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os3
Os
A
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MD_1213582242930949697188121
2024-08-16T14:20:18
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8118725040347786981884054
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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[ 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
Os16
Os
A
[ 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76 ]
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[ "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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CO_8122297470238565134361752
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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CO_8122297470238565134361752
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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MD_1213582242930949697188121
2024-08-16T15:13:01
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_8_12" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8135226810724034199104791
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
2024-08-16T15:15:11
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter1_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_5_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8160827863525630099533996
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
2024-08-16T14:24:55
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2023-12-01T22:55:38
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CO_8163879855855002015956776
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:21:25
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2023-12-01T22:55:38
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CO_8166477318991263837008744
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_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_3_19" ]
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2023-12-01T22:55:38
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CO_8167902897549771100629687
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
2024-08-16T15:07:36
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PO_7327155792315857476169392
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_6_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8168302676752146599289348
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
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Os
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MD_1213582242930949697188121
2024-08-16T14:43:23
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_5_4" ]
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2023-12-01T22:55:38
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CO_8192635381533824197432866
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
2024-08-16T14:58:26
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_10_13" ]
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2023-12-01T22:55:38
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CO_8236682240194474042582918
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:40:00
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PO_5793400113680851715241581
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_2_13" ]
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2023-12-01T22:55:38
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CO_8255310941773766171167373
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:55:55
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_4_14" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8262157320416521131206716
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
2024-08-16T14:39:22
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_0_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8265609798394537335128844
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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{'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
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MD_1213582242930949697188121
2024-08-16T15:36:10
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PO_5003527789215758883205140
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_vacancies_Vac_0_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8271607975964494746139039
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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[ 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
2024-08-16T15:26:25
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PO_8824999899756360104306085
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MD_1303044916320138948604021
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_9_825_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8292490975339241684903366
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
Os31
Os
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MD_1213582242930949697188121
2024-08-16T15:41:24
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_vacancies_Vac_0_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8298985119092890667173116
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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MD_1213582242930949697188121
2024-08-16T14:56:40
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MD_1128333416791028182801865
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CO_8299651339100774066548193
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:04:01
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_6_11" ]
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2023-12-01T22:55:38
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CO_8301289957682624938310249
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
2024-08-16T14:26:37
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PO_1136054829689894539541073
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_4_19" ]
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2023-12-01T22:55:38
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CO_8314512425544510652272806
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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2024-08-16T15:14:52
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null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_dbP2_18" ]
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2023-12-01T22:55:38
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CO_8325175758311923662524863
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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2024-08-16T14:26:27
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2023-12-01T22:55:38
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CO_8341052504632135755753093
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
2024-08-16T14:40:54
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_11_10" ]
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2023-12-01T22:55:38
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CO_8357286241794354250312471
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:25:28
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_7_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8363537981644838368559666
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
2024-08-16T14:55:47
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PO_9977373413184953535348198
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_11_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8367058273166356754391297
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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2024-08-16T14:37:35
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8383195648944080762995289
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
2024-08-16T14:41:18
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PO_1068128735655063492368467
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MD_1128333416791028182801865
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2023-12-01T22:55:38
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CO_8398165392646271852016171
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
2024-08-16T14:41:00
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PO_4750503593068529480871514
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_interTdB_3300_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8410740253772799446212577
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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[ [ 1, 1, 1 ] ]
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os7
Os
A
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MD_1213582242930949697188121
2024-08-16T15:24:49
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PO_3779459042669655025417872
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MD_4076060147778651875063260
null
[ "Os_iter_all_Os_iter1_2_mp-1080694_vacancies_Vac_0_7" ]
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2023-12-01T22:55:38
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CO_8448165923453807982117699
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
2024-08-16T15:37:32
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PO_1136882726288431643009389
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_crowdionP_825_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8460328433830589094846601
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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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
2024-08-16T14:43:54
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_11_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8473027100016727910723440
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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MD_1213582242930949697188121
2024-08-16T14:41:53
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_2_3" ]
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2023-12-01T22:55:38
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CO_8497100978394558722406745
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
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MD_1213582242930949697188121
2024-08-16T15:39:37
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interOhB_4" ]
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2023-12-01T22:55:38
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CO_8497985112138479132145192
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
2024-08-16T15:04:26
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PO_9979690564544863531811575
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_dbPP_825_4" ]
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2023-12-01T22:55:38
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CO_8510559017616877245813275
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
2024-08-16T15:09:30
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_4_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8517253678746984491563963
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
2024-08-16T14:56:40
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PO_1184573146639644166598714
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_1_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8524162144489697859244355
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
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2024-08-16T14:23:48
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null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_dbP2_5" ]
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2023-12-01T22:55:38
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CO_8526078057698868487860586
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
2024-08-16T15:02:59
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8529971483926778985559805
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
2024-08-16T15:02:59
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[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_15", "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_opt_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8529971483926778985559805
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
2024-08-16T14:52:58
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_11_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8547960687828977113016674
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
2024-08-16T14:42:06
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PO_1200105427624154084222866
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_4_14" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8553942469361225259457554
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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2024-08-16T15:02:58
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[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_5_15" ]
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2023-12-01T22:55:38
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CO_8596455130634341728780374
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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2024-08-16T14:47:52
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2023-12-01T22:55:38
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CO_8624168689893845827061318
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_iter_all_Os_iter1_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_9_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8640468027492786849870545
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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23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:18:29
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_10_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8643343527850380543940525
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
2024-08-16T14:46:10
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_5_16" ]
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2023-12-01T22:55:38
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CO_8653216794207573393600059
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
2024-08-16T14:24:31
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PO_3519842731027320958303411
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_dbP_3300_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8665020978542006017989224
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
2024-08-16T14:23:26
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_9_13" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8674553886654036758862321
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:07:43
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MD_1197491105352459872634686
null
[ "Os_iter_all_Os_iter3_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_5_825_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8710930835023573216152127
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
2024-08-16T14:47:43
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_7_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8711767952190211818387173
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T15:27:03
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2023-12-01T22:55:38
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CO_8713181586801198956946698
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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2024-08-16T14:57:07
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2023-12-01T22:55:38
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CO_8723185218448376616103297
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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2024-08-16T14:48:44
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[ "Os_iter_all_Os_iter1_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_6_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8725814316143987465431409
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
2024-08-16T15:28:14
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter1_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_2_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8733588892769399412757847
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T15:09:14
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter1_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_2_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8755110283243933516027198
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
2024-08-16T14:28:22
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PO_1776986255404581676003148
{"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_9_3300_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8762363160978674951698265
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T15:07:05
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CO_8785229410688106063971802
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
2024-08-16T15:06:04
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_dbP2_8" ]
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2023-12-01T22:55:38
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CO_8785843444509159535253614
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
2024-08-16T14:42:57
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PO_4769034454344986894196982
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_3_3300_13" ]
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2023-12-01T22:55:38
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CO_8787237662144683689918988
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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2024-08-16T14:23:48
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_10_14" ]
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2023-12-01T22:55:38
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CO_8811938377206548018326862
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
2024-08-16T14:28:39
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null
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2023-12-01T22:55:38
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CO_8826376817863907085397067
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
2024-08-16T14:58:08
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MD_4076060147778651875063260
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2023-12-01T22:55:38
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CO_8827407613009528590976164
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
2024-08-16T14:37:56
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_9_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8856340148864294475985451
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:38:05
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_2_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8866890233253718712000156
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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[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_10_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8878946717430071338758656
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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2024-08-16T15:15:51
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[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_11_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8882886529927262274711498
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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2024-08-16T14:49:59
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2023-12-01T22:55:38
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CO_8892759244477983260702895
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
Os17
Os
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MD_1213582242930949697188121
2024-08-16T15:39:32
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdionB2_18" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8894375714108557415912015
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
Os31
Os
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2024-08-16T15:36:14
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MD_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8905121119545394715632892
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:25:25
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8920140882592275819548036
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
2024-08-16T14:24:00
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_5_11" ]
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2023-12-01T22:55:38
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CO_8930302483915420124885626
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:28:50
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[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_dbP2_3300_5" ]
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2023-12-01T22:55:38
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CO_8932551655123599446888081
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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2024-08-16T14:41:20
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2023-12-01T22:55:38
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CO_8945103136379648189869563
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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2024-08-16T14:41:20
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2023-12-01T22:55:38
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CO_8945103136379648189869563
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
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[ "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_8950491941757937500581570
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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CO_8950491941757937500581570
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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CO_8957499119744040718205467
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
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:29:31
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_8976087231445591406292095
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:42:22
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PO_1220431906917527771628467
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_7_8" ]
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2023-12-01T22:55:38
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CO_8996195868902885461686098
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
A
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MD_1213582242930949697188121
2024-08-16T14:28:55
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_8_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8997070109100345863678093
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
2024-08-16T15:37:08
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_dbPP_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9006741979797960710198336
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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CO_9022533203094318223566735
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:18:46
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MD_7572472347497086905713556
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[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_interOh_825_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9047819172350592651031271
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
2024-08-16T15:38:18
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_0_10" ]
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2023-12-01T22:55:38
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CO_9062129254866169872156113
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
2024-08-16T15:11:23
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_3_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9066575501805125941123398
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:25:34
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_5_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9075633746744253821967216
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