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Re16
Re
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MD_1213582242930949697188121
2024-08-16T14:26:42
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PO_8443371345280305121776641
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MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_elastic_B222_dist03_10_3500_5" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1000114035453687945788570
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
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MD_1213582242930949697188121
2024-08-16T14:56:28
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PO_1294334285713454397095729
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MD_8072777543375650454349539
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[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1000631778461373576782911
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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2024-08-16T14:14:22
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2023-12-01T22:58:16
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CO_1001242683918952123304000
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:13:06
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PO_7270560651028793334872083
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_dbB_875_15" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1001249599863286595221786
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T14:59:34
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PO_1098888252512309498689017
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MD_8072777543375650454349539
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[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_7_13", "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_7_18" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1001762425091954849201315
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
A
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MD_1213582242930949697188121
2024-08-16T14:59:39
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
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MD_1213582242930949697188121
2024-08-16T15:22:36
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MD_1951564499902567866502008
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2023-12-01T22:58:16
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CO_1004253876927435229937987
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T15:21:02
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PO_1496534168650056774637949
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_5_875_2" ]
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2023-12-01T22:58:16
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CO_1004371655486693383092200
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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CO_1004491628045547733878883
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
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MD_1213582242930949697188121
2024-08-16T15:20:08
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PO_6461942960457313219673975
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MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_elastic_B222_dist03_1_3500_5" ]
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2023-12-01T22:58:16
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CO_1004921410329665001744622
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re31
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MD_1213582242930949697188121
2024-08-16T15:12:46
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PO_5087249132266569786206337
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MD_4820518588507787498309475
null
[ "Re_iter1_3_mp-8642_vacancies_Vac_0_875_12" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1009785276822745288841406
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:24:15
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2023-12-01T22:58:16
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:31:12
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1012325131434346618802586
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
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MD_1213582242930949697188121
2024-08-16T14:12:35
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_2_875_14" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1012511206707758015278079
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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Re
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2024-08-16T14:14:58
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1014151797435894241517333
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:12:44
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2023-12-01T22:58:16
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CO_1015186540737485772568846
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
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MD_1213582242930949697188121
2024-08-16T14:13:11
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MD_1951564499902567866502008
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2023-12-01T22:58:16
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CO_1015376213913317854136271
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:17:16
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_7_875_4" ]
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2023-12-01T22:58:16
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CO_1015446956553525376174715
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
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MD_1213582242930949697188121
2024-08-16T15:14:08
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[ "Re_iter2_0_mp-8_elastic_B222_dist03_9_3500_6" ]
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2023-12-01T22:58:16
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CO_1018363235553375861693313
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
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MD_1213582242930949697188121
2024-08-16T15:20:40
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MD_1951564499902567866502008
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2023-12-01T22:58:16
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CO_1019665032152927249545464
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
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MD_1213582242930949697188121
2024-08-16T15:13:31
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2023-12-01T22:58:16
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CO_1022168287379609525245554
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:34:18
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2023-12-01T22:58:16
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23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
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MD_1213582242930949697188121
2024-08-16T15:22:09
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[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1024502565509369306651920
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:35:09
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PO_7494952950204244832463125
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MD_3140906615584827818889926
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[ "Re_iter0_T875_0_mp-8_interstitials_HCP2_db_9", "Re_iter0_T875_0_mp-8_interstitials_HCP2_db_26", "Re_iter0_T875_0_mp-8_interstitials_HCP2_db_28" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1026059149759006639361881
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
[ [ 1, 1, 1 ] ]
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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MD_1213582242930949697188121
2024-08-16T14:12:56
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PO_9731414383387426703516628
{"materials-project-id": "mp-8642", "temperature": 3500, "hash": "2333412701806194962250672412351887755010813328886382891008025698246224040567077662483682371323617452689980898265035030575180496515195647187485047238158109", "id": "MD_2333412701806194962250672"}
MD_2333412701806194962250672
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_3_3500_8" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1027773660548207185093497
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:30
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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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:45:23
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MD_5276451162749980934843793
null
[ "Re_iter0_T875_3_mp-8642_elastic_B222_dist03_7_4", "Re_iter0_T875_3_mp-8642_elastic_B222_dist03_7_15" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1027917656075046111668281
23-Single-Element-DNPs_RSCDD_2023-Re
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Re" ]
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-208.974685
8,714.473585
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2023-12-01T17:58:30
[ [ 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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
End of preview. Expand in Data Studio

Dataset

23-Single-Element-DNPs RSCDD 2023-Re

Description

Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

Additional details stored in dataset columns prepended with "dataset_".

Dataset authors

Christopher M. Andolina, Wissam A. Saidi

Publication

https://doi.org/10.1039/D3DD00046J

Original data link

https://github.com/saidigroup/23-Single-Element-DNPs

License

gpl-3.0

Number of unique molecular configurations

5029

Number of atoms

101248

Elements included

Re

Properties included

energy, atomic forces, cauchy stress

Cite this dataset

Andolina, C. M., and Saidi, W. A. 23-Single-Element-DNPs RSCDD 2023-Re. ColabFit, 2023. https://doi.org/10.60732/1e0997f8

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