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

Dataset card Data Studio Files
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2024-08-16T14:33:03
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MD_7572472347497086905713556
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2023-12-01T22:55:38
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CO_7247637494286471315224136
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T14:31:34
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2023-12-01T22:55:38
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CO_7251638207235938251529053
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:37:16
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2023-12-01T22:55:38
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CO_7256884587541687582135677
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:42:02
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PO_1162318231551183855636323
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdion_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7263436942897527802882668
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:24:38
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PO_1797970187324278977738814
{"materials-project-id": "mp-8643", "hash": "1128333416791028182801865069200427139300450021725105332188854259916791510835379177362950532556344828249950796760259977283249586702380288540112988627786633", "id": "MD_1128333416791028182801865"}
MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_2_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7274474634156627430891794
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:42:07
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7279433885640877458492686
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7294058389966581590980690
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:00:48
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CO_7299216630236372210864773
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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Os
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MD_1213582242930949697188121
2024-08-16T15:40:21
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MD_3410785766819930157739133
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2023-12-01T22:55:38
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CO_7299305812314830608046064
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:42:57
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PO_7328432888201133284328805
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_db_3300_9" ]
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2023-12-01T22:55:38
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CO_7327744200864965855225451
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T14:30:52
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_2_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7330161925792881156096757
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T15:35:29
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdionB_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7330454363505045311217635
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os16
Os
A
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2024-08-16T15:10:09
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_6_0" ]
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2023-12-01T22:55:38
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CO_7331993523462720273080965
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:17:00
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MD_1303044916320138948604021
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_3_825_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7348548084117081466333074
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T15:31:58
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_2_13" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7357515751694287978128878
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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MD_1213582242930949697188121
2024-08-16T14:49:08
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PO_1326092940456908365829554
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interOh_19" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7359960863170045603314293
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:07:11
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PO_2852527200455714670252775
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MD_1303044916320138948604021
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_5_825_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7378043273101904987707799
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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CO_7381631197648707417923630
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:47:37
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2023-12-01T22:55:38
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CO_7383458461066796857044969
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:55:04
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdionB_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7385923120836374830105819
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:31:25
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2023-12-01T22:55:38
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CO_7387565464797311589327945
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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MD_1213582242930949697188121
2024-08-16T14:42:01
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_7408698320878192343936144
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:11:30
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_3_15" ]
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2023-12-01T22:55:38
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CO_7413928874854640629443156
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:39:40
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2023-12-01T22:55:38
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CO_7418477739472174773674582
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:39:26
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PO_7543466657994496882430063
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_0_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7418586350490997711078314
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_1150511407299699978252272
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2023-12-01T22:55:38
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CO_7422501975579565841718288
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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null
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2023-12-01T22:55:38
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CO_7426893271740814981930144
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:32:33
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MD_7572472347497086905713556
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_interTdB_825_1" ]
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2023-12-01T22:55:38
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CO_7428597258312844278679093
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:32:17
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PO_4953748916126083889625588
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdionB2_14" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7429068798754448155896311
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os31
Os
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MD_1213582242930949697188121
2024-08-16T15:30:56
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PO_1168702644002251303104290
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_vacancies_Vac_0_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7448960878852616944277807
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T14:47:18
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null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_interOhB_7" ]
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2023-12-01T22:55:38
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CO_7452816774584437521265027
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:16:35
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7471257275860568201780950
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_5_11" ]
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2023-12-01T22:55:38
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CO_7472905176818300487179317
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:36:34
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MD_1086845055867124744315202
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2023-12-01T22:55:38
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CO_7498206401209123021219490
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:31:51
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_3_17" ]
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2023-12-01T22:55:38
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CO_7498549719550272681681567
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T14:55:21
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2023-12-01T22:55:38
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CO_7503754144768354995783030
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
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MD_1213582242930949697188121
2024-08-16T14:32:28
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdionB2_12" ]
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2023-12-01T22:55:38
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CO_7539352944750200737017015
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T14:29:55
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PO_5088762289478040099817719
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_4_4" ]
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2023-12-01T22:55:38
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CO_7559369687710745394656697
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:17:24
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23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
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MD_3410785766819930157739133
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2023-12-01T22:55:38
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CO_7566888585816543332285121
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:30:07
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_7573819992396138003726726
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T15:34:57
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PO_9045110978545961620981732
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_2_3300_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7582613007380644411775379
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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MD_1213582242930949697188121
2024-08-16T14:27:25
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PO_2217330253236331202980096
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_10_0" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7599956007835631418216299
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:55:42
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_crowdionP_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7608709140478029841924565
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:40:22
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter1_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_4_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7625944761088931429811509
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:08:06
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_4_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7628779634461754967481589
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:44:11
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PO_1136231611017185085923584
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter0_T825_1_mp-8643_elastic_B222_dist03_2_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7661230835533347488148400
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:42:32
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PO_7043372177706806917899107
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_interstitials_HCP2_interOh_3300_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7671786817446122045811291
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T14:31:40
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_db_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7704656582006474133714290
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:50:34
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PO_5431050628833980185781675
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_6_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7714161502458834987970659
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:12:23
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_6_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7738834676048650496702541
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:31:19
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdionB_6" ]
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2023-12-01T22:55:38
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CO_7764169285023250181825821
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:48:37
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2023-12-01T22:55:38
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CO_7768494054320453101652653
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:39:11
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PO_6581833467921487074666738
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_interstitials_HCP2_db_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7793661083098513090447842
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os32
Os
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MD_1213582242930949697188121
2024-08-16T14:40:32
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PO_3282132144602981796345296
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_11_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
7796576958668858183100343728915464899460404191729881777737877953629144948733774867312481457192278795498919915433339580506070469987733045907613164398398615
CO_7796576958668858183100343
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
A
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MD_1213582242930949697188121
2024-08-16T15:11:17
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_10_10" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7802613386637873595278601
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
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2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T14:51:34
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null
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2023-12-01T22:55:38
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CO_7806464960615599649753565
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:28:45
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MD_7572472347497086905713556
null
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2023-12-01T22:55:38
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CO_7806497620892417187582856
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:31:15
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PO_9790316750830989985672762
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_dbP2_1" ]
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2023-12-01T22:55:38
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CO_7827127987412437813399143
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:31:43
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_7_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7854378825527398227572070
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:35:33
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_10_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7858799938599767464630693
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:31:19
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CO_7859518631546582594641038
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:17:12
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdion_3" ]
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2023-12-01T22:55:38
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CO_7859555863787706814684402
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:09:09
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PO_7717384168827769976641421
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_3_3300_18" ]
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2023-12-01T22:55:38
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CO_7881424087493924935738350
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:04:32
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MD_8059406656008618914882983
null
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2023-12-01T22:55:38
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CO_7892958818016584274474874
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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MD_1213582242930949697188121
2024-08-16T14:30:50
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter1_1_mp-8643_elastic_B222_dist03_8_0" ]
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2023-12-01T22:55:38
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CO_7894896916524654837005625
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:53:18
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PO_4131210667677143330304050
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_2_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7903348153428140045753238
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T14:31:10
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_11_19" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7905676727394886272387256
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T15:28:51
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_interTdB_12" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7910517834580190392292462
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os15
Os
A
[ 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76 ]
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MD_1213582242930949697188121
2024-08-16T15:09:36
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PO_8832941170766053782507136
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_vacancies_Vac_0_2" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7921089015179918348117638
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os
Os
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VASP
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MD_1213582242930949697188121
2024-08-16T15:23:36
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PO_3787592752262100021576817
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_9" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_7971916016013735992615293
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:11:45
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MD_1086845055867124744315202
null
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8007613899034791065623581
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:35:44
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter2_1_mp-8643_elastic_B222_dist03_1_0" ]
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2023-12-01T22:55:38
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CO_8010074691164779575218350
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:32:40
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_11" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8026563519902199013315028
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:20:47
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T3300_1_mp-8643_elastic_B222_dist03_5_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8033392337973405009257333
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T15:12:06
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PO_7960835342855478355805612
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_7_5" ]
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2023-12-01T22:55:38
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CO_8035657451385770219678846
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T15:30:35
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PO_2359429022255940737611782
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_7_3300_1" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8049489250573038794259600
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
[ 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76 ]
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1
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MD_1213582242930949697188121
2024-08-16T14:26:17
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PO_3522964470292428972412399
{"materials-project-id": "mp-49", "hash": "3410785766819930157739133602960296775422439544612365590214994635763169177363191627840577432795366525135535563843886558553779195323694767533261615769563450", "id": "MD_3410785766819930157739133"}
MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter2_0_mp-49_interstitials_HCP2_crowdion_7" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8050825380076533530130178
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
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4,779
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2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
[ 3 ]
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[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T15:28:02
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_11_15" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8056502195166899979384052
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:36:12
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T3300_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_11_18" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8061875724173497277519721
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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CO_8086266333415667784918796
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:36:21
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MD_3410785766819930157739133
null
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2023-12-01T22:55:38
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CO_8097281486438141594354412
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
null
[ "Os_iter_all_Os_iter2_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_5" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8111907914756265042366927
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_3410785766819930157739133
null
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CO_8113922096894123880065629
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
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MD_1213582242930949697188121
2024-08-16T15:09:49
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_7_0" ]
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2023-12-01T22:55:38
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CO_8122832924317069719326179
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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2024-08-16T15:15:38
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MD_1128333416791028182801865
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[ "Os_iter_all_Os_iter0_T825_1_mp-8643_vacancies_Vac_0_15" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8123724814951357673426232
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os32
Os
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2024-08-16T14:54:58
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8169564436420533515777471
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os17
Os
A
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MD_1213582242930949697188121
2024-08-16T15:39:23
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T3300_0_mp-49_interstitials_HCP2_crowdionB_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8180342478005211996106273
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T15:00:20
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MD_7572472347497086905713556
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[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_9_825_4" ]
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2023-12-01T22:55:38
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CO_8202627795121593657491173
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:11:47
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter0_T825_0_mp-49_interstitials_HCP2_crowdion_16" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8214169957437448421348986
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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Os
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MD_1213582242930949697188121
2024-08-16T14:30:40
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MD_1086845055867124744315202
null
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[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8228638876922686401494385
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:43:01
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_4_w3arElPCdTvj6s3-QgGt6YXTAhGK_elastic_B222_dist03_1_13" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8241078763520171700228946
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
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Os
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MD_1213582242930949697188121
2024-08-16T14:58:20
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MD_1086845055867124744315202
null
[ "Os_iter_all_Os_iter0_T825_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_elastic_B222_dist03_7_18" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8256146431889379970080745
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:58:47
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PO_6349946766363523155125757
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MD_1150511407299699978252272
null
[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_10_3300_6" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8258415634520263558900256
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:30:38
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MD_1086845055867124744315202
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[ "Os_iter_all_Os_iter0_T3300_3_5FQY1cKaxcYqrPYN2iyvrtKPlGeh_vacancies_Vac_0_19" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8269643424194097897783790
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:34:25
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MD_1150511407299699978252272
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[ "Os_iter_all_Os_iter3_1_mp-8643_elastic_B222_dist03_3_3300_9" ]
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2023-12-01T22:55:38
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CO_8269692693662478433821025
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:35:16
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MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_11_2" ]
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2023-12-01T22:55:38
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CO_8285604387931184179215460
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:56:11
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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MD_1213582242930949697188121
2024-08-16T14:57:29
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PO_5454629324511594100628385
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MD_8059406656008618914882983
null
[ "Os_iter_all_Os_iter3_0_mp-49_elastic_B222_dist03_6_3300_5" ]
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2023-12-01T22:55:38
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CO_8285874078027528278095725
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
Os31
Os
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MD_1213582242930949697188121
2024-08-16T14:54:41
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PO_1714225734432006647417854
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MD_1128333416791028182801865
null
[ "Os_iter_all_Os_iter1_1_mp-8643_vacancies_Vac_0_8" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8289233214102759274157584
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0
Os16
Os
A
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1
VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:38:06
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PO_6479197862250839677295976
{"materials-project-id": "mp-49", "hash": "3410785766819930157739133602960296775422439544612365590214994635763169177363191627840577432795366525135535563843886558553779195323694767533261615769563450", "id": "MD_3410785766819930157739133"}
MD_3410785766819930157739133
null
[ "Os_iter_all_Os_iter1_0_mp-49_elastic_B222_dist03_1_5", "Os_iter_all_Os_iter2_0_mp-49_elastic_B222_dist03_1_7", "Os_iter_all_Os_iter0_T825_0_mp-49_elastic_B222_dist03_1_0", "Os_iter_all_Os_iter0_T3300_0_mp-49_elastic_B222_dist03_1_4" ]
[ "DS_098x6q7kbeat_0" ]
2023-12-01T22:55:38
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CO_8296258173234801885035203
23-Single-Element-DNPs_RSCDD_2023-Os
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Os from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Os" ]
1
4,779
4,779
117,968
0
4,779
0
4,779
0
4,779
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16,885.52072
0
2023-12-01T17:56:11
[ [ 1, 1, 1 ] ]
[ 3 ]
2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1ec0df98
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DS_098x6q7kbeat_0
23-Single-Element-DNPs_RSCDD_2023-Os__Andolina-Saidi__DS_098x6q7kbeat_0