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2024-08-16T15:16:01
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CO_2795604494312898800692192
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:41:24
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2023-12-01T22:52:50
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CO_8294951559554348493646599
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:34:50
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2023-12-01T22:52:50
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CO_9002429759254773446714608
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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2023-12-01T22:52:50
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CO_8161940174723040512191745
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
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MD_1213582242930949697188121
2024-08-16T15:06:06
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_1132611020499689124400237
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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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23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:11:02
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_elastic_B222_dist03_9_17" ]
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2023-12-01T22:52:50
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CO_8793148709366284498197292
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:26:37
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PO_2547889654016433106417051
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MD_7937157088987030981692291
null
[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_elastic_B222_dist03_0_12" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:50
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CO_5944569376957776595185888
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co32
Co
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MD_1213582242930949697188121
2024-08-16T14:30:23
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MD_6994839348631346930393042
null
[ "Co_iter_all_Co_iter0_450_3_mp-102_elastic_B222_dist03_8_8" ]
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2023-12-01T22:52:50
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CO_8468025897374709391506724
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:38:01
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PO_1304325678182286882464708
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MD_1061199478628841031716802
null
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2023-12-01T22:52:50
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CO_1229704129562726569289880
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:08:46
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MD_1036163058585410650666857
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2023-12-01T22:52:50
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CO_6966379051512328608219530
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T15:28:36
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PO_6506428755111092007773086
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_1765762429533319666172599
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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Co
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MD_1213582242930949697188121
2024-08-16T14:31:17
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MD_1061199478628841031716802
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CO_7985643650905683743230021
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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MD_1213582242930949697188121
2024-08-16T14:18:27
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_1121657688375794846753123
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co15
Co
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MD_1213582242930949697188121
2024-08-16T14:21:26
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PO_1010777134847061344958980
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_4115367786553545005946641
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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2023-12-01T22:52:50
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CO_1609872737999389148575089
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:52:51
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CO_2539601240480313758189842
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_7937157088987030981692291
null
[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_elastic_B222_dist03_3_7" ]
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2023-12-01T22:52:50
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CO_1037204666002261792039103
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2024-08-16T14:31:39
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2023-12-01T22:52:50
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CO_9395954821371432901969353
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:28:39
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PO_2898612811966814687867416
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_1310965219938463301597757
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:23:28
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PO_2386321614808196407503580
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_1308744284629939837957650
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co8
Co
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2024-08-16T15:12:02
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CO_3785884984132467745065081
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:19:29
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MD_1893387634103462169451603
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2023-12-01T22:52:50
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CO_1184958032028109197682944
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:38:37
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MD_6994839348631346930393042
null
[ "Co_iter_all_Co_iter0_450_3_mp-102_elastic_B222_dist03_0_17" ]
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2023-12-01T22:52:50
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CO_4084750464952623286403277
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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2024-08-16T15:03:49
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null
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CO_1303184533505841568179513
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:36:14
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MD_7937157088987030981692291
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2023-12-01T22:52:50
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CO_1115027719274784666004439
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:22:58
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PO_2752004582809429333973206
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_interstitials_HCP2_dbP2_0" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:50
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CO_4035830622943560265521793
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:54:32
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2023-12-01T22:52:50
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CO_5039174646200842794201925
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:08:54
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2023-12-01T22:52:51
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CO_7942779413205908721110447
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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2024-08-16T15:32:22
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MD_8614748966000713280909781
null
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CO_1088715821913550979590799
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:01:27
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_elastic_B222_dist03_8_16" ]
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2023-12-01T22:52:50
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CO_4823803455711660477640511
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:47:59
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MD_4769414187976683966140502
null
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2023-12-01T22:52:50
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CO_8631750281757992882736778
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:19:10
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MD_1893387634103462169451603
null
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CO_1352434719031696554709131
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:42:59
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CO_7020397521762368672573987
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
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MD_1213582242930949697188121
2024-08-16T15:15:25
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PO_3818157543050775528390672
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_interstitials_HCP2_db_16" ]
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2023-12-01T22:52:50
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CO_6632052932168252211309458
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:34:30
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MD_1893387634103462169451603
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CO_8189195469833535968527055
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_7788717455418391389520224
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:35:18
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MD_5400386851347773166444329
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2023-12-01T22:52:50
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CO_9026593326436356223019829
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:26:06
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2023-12-01T22:52:50
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CO_1106115114903384229122013
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2024-08-16T15:29:16
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CO_2656404087787698934587066
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:20:53
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_vacancies_Vac_0_1" ]
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2023-12-01T22:52:50
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CO_5778845001008469057624045
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:31:48
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PO_6046505214341045371855904
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_elastic_B222_dist03_5_15" ]
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2023-12-01T22:52:50
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CO_2625373487337133540305018
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Co" ]
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2024-08-16T14:51:18
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2023-12-01T22:52:50
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CO_1313151391073699564424498
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:17:25
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2023-12-01T22:52:50
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CO_1127325300246304491003542
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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Co
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MD_1213582242930949697188121
2024-08-16T15:20:16
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PO_2592477929373203891082193
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_3348313269051163372650517
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:25:21
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_interstitials_HCP2_interTd_8" ]
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2023-12-01T22:52:51
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CO_3149447563616829604725162
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:29:07
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MD_1893387634103462169451603
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2023-12-01T22:52:50
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CO_1035240919497896198293315
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:19:03
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_elastic_B222_dist03_2_19" ]
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2023-12-01T22:52:50
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CO_9112311407385354368898781
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:24:27
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2023-12-01T22:52:50
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CO_1035609909784563412984493
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:22:53
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_1897411009114923123704177
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:31:58
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PO_1113360703752812387566395
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_5053945011891848325970790
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:32:39
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PO_4189669764406609281466148
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MD_1061199478628841031716802
null
[ "Co_iter_all_Co_iter2_2_mp-1271679_elastic_B222_dist03_1_1800_4" ]
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2023-12-01T22:52:51
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CO_8440802829898130957515613
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:25:47
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PO_1994870766653116539252052
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_9208206541720169913516493
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:40:49
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PO_5236822976017760046016843
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MD_1061199478628841031716802
null
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2023-12-01T22:52:50
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CO_2618343574579807934689571
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:14:58
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PO_2506172393005603628229789
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[ "Co_iter_all_Co_iter0_1800_0_mp-54_elastic_B222_dist03_5_2" ]
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2023-12-01T22:52:50
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CO_1280897507489240498749096
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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2024-08-16T14:42:59
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null
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2023-12-01T22:52:50
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CO_4021161576963665925450402
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
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MD_1213582242930949697188121
2024-08-16T14:35:35
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PO_1328792058498420512845088
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MD_1061199478628841031716802
null
[ "Co_iter_all_Co_iter0_1800_2_mp-1271679_elastic_B222_dist03_10_14" ]
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2023-12-01T22:52:50
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CO_8733329217024143001765132
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:43:31
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MD_7937157088987030981692291
null
[ "Co_iter_all_Co_iter0_1800_1_mp-1183710_elastic_B222_dist03_1_4" ]
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2023-12-01T22:52:51
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CO_6086907268216986208989880
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:27:27
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MD_7937157088987030981692291
null
[ "Co_iter_all_Co_iter2_1_mp-1183710_elastic_B222_dist03_5_1800_0" ]
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2023-12-01T22:52:51
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CO_1221156918525809295664195
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T15:31:44
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PO_6848457429976239321801368
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_interstitials_HCP2_interTdB_9" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:50
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CO_1169190384634748055609074
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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2024-08-16T14:34:08
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CO_1085190641766574863599850
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:41:10
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2023-12-01T22:52:50
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CO_5002829628144942999380955
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:44:37
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PO_1417873692617043502818453
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MD_1893387634103462169451603
null
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2023-12-01T22:52:51
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CO_1043704912662868594315855
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:26:21
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23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:12:42
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2023-12-01T22:52:50
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CO_7054711259501577983380356
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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CO_1244564207163728390604480
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:30:59
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PO_8013711142692900927324086
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_9024665574315751552191128
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
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MD_1213582242930949697188121
2024-08-16T15:10:52
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PO_6956324723596927960405421
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_interstitials_HCP2_crowdionP_16" ]
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2023-12-01T22:52:50
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CO_1340475369154552378303042
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:26:56
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PO_1526835340417797631354498
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MD_6994839348631346930393042
null
[ "Co_iter_all_Co_iter0_450_3_mp-102_elastic_B222_dist03_7_2" ]
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2023-12-01T22:52:50
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CO_9512781609503463479619591
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co32
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MD_1213582242930949697188121
2024-08-16T14:19:00
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PO_1746475172512899259429338
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MD_7937157088987030981692291
null
[ "Co_iter_all_Co_iter2_1_mp-1183710_elastic_B222_dist03_5_1800_4" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:51
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CO_1137438291857992797345521
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
A
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MD_1213582242930949697188121
2024-08-16T15:29:12
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MD_1054558368679942546114670
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CO_4200856079645051222231593
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:33:59
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PO_9086990984237644979754738
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MD_1061199478628841031716802
null
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2023-12-01T22:52:50
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CO_5567510622943678644622076
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:21:10
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PO_4249115836306442360945568
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_6426812747020115106049658
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:05:57
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[ "Co_iter_all_Co_iter0_1800_7_sc_elastic_B222_dist03_9_2" ]
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2023-12-01T22:52:50
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CO_3937092054273272941688423
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:38:45
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MD_4769414187976683966140502
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2023-12-01T22:52:50
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CO_2354956074629085296837900
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T15:32:07
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PO_6309351987105912697945861
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MD_1061199478628841031716802
null
[ "Co_iter_all_Co_iter0_1800_2_mp-1271679_elastic_B222_dist03_9_4" ]
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2023-12-01T22:52:50
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CO_4559349798450816764109846
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T15:23:08
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MD_8614748966000713280909781
null
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CO_2896446670962776061741896
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:56:24
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_interstitials_HCP2_interTd_19" ]
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2023-12-01T22:52:50
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CO_1292439496276490711215642
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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Co
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MD_1213582242930949697188121
2024-08-16T15:28:58
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MD_1036163058585410650666857
null
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2023-12-01T22:52:50
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CO_5914557614906299000615063
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/15bb1dca
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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Co
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MD_1213582242930949697188121
2024-08-16T15:30:09
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PO_1978831122993099010389047
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_0" ]
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2023-12-01T22:52:50
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CO_7954790663215032347470885
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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}
10.60732/15bb1dca
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
A
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[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
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2023-12-01T22:52:50
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CO_3538488703863140089968755
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:52:50
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CO_9539778468615559443307669
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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2024-08-16T14:28:52
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2023-12-01T22:52:50
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CO_8185535885645537555527330
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:30:21
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PO_6599982636704632827370356
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2023-12-01T22:52:50
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CO_6914456122955510166480288
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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2024-08-16T15:03:11
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CO_4521387910346031110510274
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:26:48
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null
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2023-12-01T22:52:50
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CO_1082831921260770081654060
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:21:45
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PO_4396179965941523255099614
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MD_5400386851347773166444329
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2023-12-01T22:52:50
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CO_7868823560980568239528605
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:27:53
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_interstitials_HCP2_interTdB_19" ]
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2023-12-01T22:52:50
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CO_1067413007684989721030185
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T14:17:44
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MD_8614748966000713280909781
null
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2023-12-01T22:52:50
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CO_1086442111569222576281050
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T15:11:24
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PO_1434770412340475746611177
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MD_1893387634103462169451603
null
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2023-12-01T22:52:50
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CO_1163592060068674619297475
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T15:16:50
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MD_1061199478628841031716802
null
[ "Co_iter_all_Co_iter0_1800_2_mp-1271679_elastic_B222_dist03_11_16" ]
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2023-12-01T22:52:51
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CO_5793306722776146929909053
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
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MD_1213582242930949697188121
2024-08-16T14:49:44
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PO_7576426057451632095529038
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter2_0_mp-54_interstitials_HCP2_db_1800_2" ]
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2023-12-01T22:52:50
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CO_5919419024410287148354238
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
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MD_1213582242930949697188121
2024-08-16T14:46:00
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PO_2763607967451273256120903
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MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter2_0_mp-54_elastic_B222_dist03_5_1800_4" ]
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2023-12-01T22:52:50
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CO_9942979652061381928968580
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co17
Co
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MD_1213582242930949697188121
2024-08-16T15:23:33
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PO_5178745922799195035004660
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_interstitials_HCP2_dbB_14" ]
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2023-12-01T22:52:51
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CO_1002654369062231128807229
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:06:23
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PO_1065530357044411433925026
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MD_7937157088987030981692291
null
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2023-12-01T22:52:50
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CO_7098297692302532153347688
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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MD_1213582242930949697188121
2024-08-16T15:16:53
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PO_3290955247509316530427310
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MD_6642807180879329290153248
null
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2023-12-01T22:52:50
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CO_7667144270996540918377167
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
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Co
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MD_1213582242930949697188121
2024-08-16T14:57:33
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MD_8614748966000713280909781
null
[ "Co_iter_all_Co_iter0_450_0_mp-54_interstitials_HCP2_crowdionB_12" ]
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2023-12-01T22:52:50
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CO_1251103921113483650162444
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co8
Co
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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:30:06
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PO_4444416948732428339447392
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MD_1036163058585410650666857
null
[ "Co_iter_all_Co_iter0_1800_7_sc_elastic_B222_dist03_3_3" ]
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2023-12-01T22:52:50
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CO_1208876584754048950446172
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:53:02
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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}
10.60732/15bb1dca
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0
Co16
Co
A
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:21:16
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PO_6920129500589446281100075
{"materials-project-id": "mp-54", "temperature": 1800, "hash": "1893387634103462169451603323598526632651272843282251728201860355027330448453005995201064119702139930735968655348319445642307542291830043980251168027155027", "id": "MD_1893387634103462169451603"}
MD_1893387634103462169451603
null
[ "Co_iter_all_Co_iter0_1800_0_mp-54_elastic_B222_dist03_11_13" ]
[ "DS_jt0lax9yd15r_0" ]
2023-12-01T22:52:51
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CO_9090887046686539327090740
23-Single-Element-DNPs_RSCDD_2023-Co
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Co from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Co" ]
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2023-12-01T17:53:02
[ [ 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}
10.60732/15bb1dca
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DS_jt0lax9yd15r_0
23-Single-Element-DNPs_RSCDD_2023-Co__Andolina-Saidi__DS_jt0lax9yd15r_0