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

Dataset card Data Studio Files
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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
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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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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
Os15
Os
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MD_1213582242930949697188121
2024-08-16T14:27:12
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PO_1194320222060460545619627
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_vacancies_Vac_0_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9114709840003683536724850
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:29:54
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_9_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9123155800135362513728118
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T14:45:56
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[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_0_19" ]
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2023-12-01T22:55:38
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CO_9130460945171072344737700
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:35:06
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2023-12-01T22:55:38
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CO_9134911882844071188873925
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:25:13
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_dbP_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9135095180354308838740320
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_1086845055867124744315202
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[ "Os_iter_all_Os_iter2_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_10_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9145727921131331856850240
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_1086845055867124744315202
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2023-12-01T22:55:38
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CO_9157758821707076744916685
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:21:39
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PO_8891621065127586517588397
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_3_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9171661490186138165516180
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:56:01
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PO_1171788497393059839588498
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MD_1303044916320138948604021
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_3_825_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9194380848837838937889080
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
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2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
[ 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76 ]
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23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:25:08
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_interTd_9" ]
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2023-12-01T22:55:38
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CO_9209510771748296727868743
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2024-08-16T15:10:37
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MD_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9230289585488621229664612
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:10:37
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9232733102816596588861997
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:25:55
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MD_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9235876108365188748982955
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
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2023-12-01T22:55:38
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CO_9238622857319919990163155
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_1086845055867124744315202
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2023-12-01T22:55:38
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CO_9242816107260963726794505
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:17:58
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_4_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9285201697199037147230098
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdionB_19" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9286797206909846411782135
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
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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
2024-08-16T15:13:31
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MD_1150511407299699978252272
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[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_5_3300_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9295065958874778489592551
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:42:49
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_3_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9299470636827928829045044
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:27:21
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_3_17" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9309518354905828864926314
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:17:54
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_6_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9321138786309043815695154
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os31
Os
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2024-08-16T14:57:06
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MD_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9334468537808012289975355
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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Os
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MD_1213582242930949697188121
2024-08-16T15:00:52
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PO_4248854334781749514283959
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_interTd_825_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9355072845438690906495752
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:26:33
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PO_1227229106546443702714479
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_7_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9355384404841564335070017
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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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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2023-12-01T22:55:38
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CO_9361452537215368940389030
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T15:41:47
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MD_1086845055867124744315202
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2023-12-01T22:55:38
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CO_9364946730425641379906398
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_1_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9365956871288142950506892
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:47:32
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter2_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_3_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9366964266594697888306337
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
A
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MD_1213582242930949697188121
2024-08-16T15:03:29
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_dbP_825_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9390021788416934244529359
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:27:58
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PO_2101043950605389661746391
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_2_9" ]
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2023-12-01T22:55:38
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CO_9396704616062860805317020
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:03:56
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9399755546528158897120772
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T15:18:17
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_dbB_13" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9404636533421447196029041
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:47:46
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null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdionP_10" ]
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2023-12-01T22:55:38
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CO_9405110389707105714653302
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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MD_1213582242930949697188121
2024-08-16T15:28:08
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_4_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9413530818803208851836714
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9419831926688009251936552
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2024-08-16T14:26:30
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_8_11" ]
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2023-12-01T22:55:38
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CO_9430509093187622465798301
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T15:14:27
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_9436862449872532342275944
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:46:01
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[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_4_8" ]
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2023-12-01T22:55:38
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CO_9439997309881561340490244
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:55:22
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_dbB_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9447931423041053235842253
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:27:22
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MD_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9460940847247234225496521
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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[ "Os_iter_all_Os_iter1_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_3_7" ]
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CO_9473161881939353633761387
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:12:16
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interTdB_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9476778870809676068914670
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:37:48
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_5_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
9485253666338804585764996912889749869295467828166139265211122557587548870535360236183648835356625459319058593854699150564175660698389046549748270652610751
CO_9485253666338804585764996
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:41:47
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_3_18" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9496763895965204716358167
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_1086845055867124744315202
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9507864089013423839695742
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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MD_1213582242930949697188121
2024-08-16T14:41:52
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_7_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9513874294002189834112153
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:18:04
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PO_1269360410269063717408073
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MD_1118551595725510582628862
null
[ "Os_iter_all_Os_iter3_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_5_3300_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9519680456125683490689553
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2023-12-01T22:55:38
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CO_9531748570610889441670446
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:40:52
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2023-12-01T22:55:38
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CO_9534429130771207606290524
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_9568062074883759343833921
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_3410785766819930157739133
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2023-12-01T22:55:38
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CO_9598955778706088232531388
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2023-12-01T22:55:38
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CO_9600148139780742420924993
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:46:15
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_2_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9604487302178473508056339
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os
Os
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MD_1213582242930949697188121
2024-08-16T15:25:43
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter2_1_mp-8643_8" ]
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2023-12-01T22:55:38
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CO_9606398330936763416544758
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T14:31:22
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_5_9" ]
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2023-12-01T22:55:38
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CO_9613790006591480776408684
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2023-12-01T22:55:38
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CO_9634861713493225480179533
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
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MD_1213582242930949697188121
2024-08-16T15:18:17
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MD_3410785766819930157739133
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[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_3_4" ]
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2023-12-01T22:55:38
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CO_9653339951503030937816115
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:17:53
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2023-12-01T22:55:38
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CO_9691338263813322729346181
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_6_12" ]
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2023-12-01T22:55:38
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CO_9700476971547206716816459
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2024-08-16T15:15:19
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_2_1" ]
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2023-12-01T22:55:38
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CO_9712061392658970785270540
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:21:26
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_dbP2_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9721614942263746322579313
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:26:03
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[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_interOhB_4" ]
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2023-12-01T22:55:38
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CO_9728616608311224418373718
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:59:38
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PO_1180765031245103905333966
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_7_3300_6" ]
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2023-12-01T22:55:38
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CO_9730992635804242086630154
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:38:14
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9736191273769935758325980
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:23:27
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_11_17" ]
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2023-12-01T22:55:38
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CO_9749759505114105088046534
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os3
Os
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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T14:28:30
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter1_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9766151407920881140624858
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:42:03
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_9_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9772439064005480138384410
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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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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CO_9777767800691768557691995
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:41:11
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_interTdB_6" ]
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2023-12-01T22:55:38
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CO_9779497682656648862901392
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:43:56
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CO_9796623361022789736158941
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os15
Os
A
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MD_1213582242930949697188121
2024-08-16T15:38:47
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_9805876256165344114556228
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:41:38
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_0_7" ]
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2023-12-01T22:55:38
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CO_9820606677369018392254622
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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CO_9832789248202183422686364
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:49:44
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_9_5" ]
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2023-12-01T22:55:38
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CO_9837784240913154324101893
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:25:37
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MD_1086845055867124744315202
null
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9867624936368724640073564
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:42:03
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PO_1134369941591443625889483
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_8_0" ]
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2023-12-01T22:55:38
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CO_9878756966687476977408969
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:20:34
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_6_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9902617703729125982262325
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:01:58
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_9_13" ]
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2023-12-01T22:55:38
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CO_9903054182432760844530347
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:31:47
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_9_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9910428138072988598106680
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:48:05
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PO_3779726960019183065768889
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_dbPP_14" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9912921345963495843008422
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2023-12-01T22:55:38
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CO_9924239162427536761401083
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
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2024-08-16T15:31:08
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_9954703486150471679568410
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
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2024-08-16T15:08:03
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MD_3410785766819930157739133
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[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_0_13" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9956324465990320446925958
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:03:05
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_5_19" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9961238946724624657069945
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:02:56
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MD_1086845055867124744315202
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2023-12-01T22:55:38
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CO_9971646894791918894598517
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os32
Os
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MD_1213582242930949697188121
2024-08-16T15:02:56
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter2_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_1_1", "Os_iter_all_Os_iter1_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_1_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9971646894791918894598517
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:27:09
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_3_17" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_9976514985606389991767823
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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CO_9984601178976210077959332
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:16:42
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_8_3300_3" ]
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2023-12-01T22:55:38
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CO_1000850630559189010678863
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
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MD_1213582242930949697188121
2024-08-16T15:09:33
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_9_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_1002042118593408150142207
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:24:10
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter1_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_8_3" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_1002896923084511229928146
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:01:52
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_10_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_1004676608927590857927582
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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DFT-PBE
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[ [ 7.899835586547852, 6.322292327880859, 4.557818412780762 ], [ 7.593477725982666, 6.387735843658447, 4.3319926261901855 ], [ 0.08008161187171936, 1.4873380661010742, -2.0683670043945312 ], [ 0.0420796200633049, 1.4128159284591675, -2.128662109375 ], [ 0.18225201964378357, 11.569609642028809, 11.510005950927734 ], [ -0.1932612657546997, 11.309155464172363, 11.472058296203613 ], [ -7.858284950256348, 6.285920143127441, 4.445627689361572 ], [ -7.565855979919434, 6.481657028198242, 4.496400833129883 ], [ 8.037543296813965, -6.470679759979248, -4.417878150939941 ], [ 7.768405914306641, -6.2851457595825195, -4.524028301239014 ], [ 0.013685449957847595, -11.251867294311523, -11.365418434143066 ], [ -0.16198909282684326, -11.47913646697998, -11.486248970031738 ], [ -0.010306299664080143, -1.5019880533218384, 2.0651187896728516 ], [ 0.06274157017469406, -1.594454288482666, 2.107740879058838 ], [ -7.894575595855713, -6.266046524047852, -4.3753533363342285 ], [ -7.995802879333496, -6.407191276550293, -4.6207427978515625 ] ]
null
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{"input": {"ALGO": "fast", "EDIFF": "1E-8", "ENCUT": "400", "IBRION": "0", "ICHARG": "0", "ISIF": "2", "ISMEAR": "1", "ISTART": "0", "ISYM": "0", "KBLOCK": "10", "KGAMMA": "F", "KPAR": "16", "KSPACING": "0.24", "LCHARG": "T", "LREAL": "F", "LWAVE": "F", "MAXMIX": "50", "NBLOCK": "1", "NELM": "200", "NELMIN": "4", "NPAR": "8", "POTIM": "2", "PREC": "A", "PSTRESS": "0", "SIGMA": "0.15", "SMASS": "-1", "file-type": "INCAR"}, "hash": "12135822429309496971881212100548754870478961791137930949625877367285087883313386750731592539663054471050405358418449513543996992751906584969573924479043013", "id": "MD_1213582242930949697188121"}
MD_1213582242930949697188121
2024-08-16T15:25:27
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PO_5258366853980121478493547
{"materials-project-id": "mp-49", "hash": "3410785766819930157739133602960296775422439544612365590214994635763169177363191627840577432795366525135535563843886558553779195323694767533261615769563450", "id": "MD_3410785766819930157739133"}
MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_9_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
1005403456865279413445692298138806556080198721822229428916812025930544531532819437166571311277203187043848679892418684379658439317860468508574156768323273
CO_1005403456865279413445692
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
1
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117,968
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4,779
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4,779
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4,779
-207.800307
16,885.52072
0
2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
[ 3 ]
2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
3310305333373179395184373908907465024750856728734418909662937810603785626298670891195529851311793949595060868418647898387050878085548765620035810912218936
DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0