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MD_1213582242930949697188121
2024-08-16T14:26:42
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MD_3894327761601644436733559
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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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DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T14:56:28
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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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DS_gzbvdicu231p_0
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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
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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
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MD_1213582242930949697188121
2024-08-16T14:12:56
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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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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.
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2023-12-01T17:58:30
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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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
2024-08-16T15:12:19
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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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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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2024-08-16T14:57:03
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2023-12-01T22:58:16
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CO_1033224032817280289964901
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
2024-08-16T14:55:32
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1033382081149521588909499
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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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
2024-08-16T15:13:59
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1034578647620914703188008
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
2024-08-16T14:35:59
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MD_2333412701806194962250672
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2023-12-01T22:58:16
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CO_1035771718816797043943842
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
2024-08-16T15:14:57
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_interstitials_HCP2_crowdion_12" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1035897627933279466683450
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}
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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
2024-08-16T14:14:21
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PO_6594348791580668890268262
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_5_9" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1037048328809418171803416
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
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MD_1213582242930949697188121
2024-08-16T14:53:25
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1037653372247987897343437
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}
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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
2024-08-16T14:33:57
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_dbP_875_14" ]
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2023-12-01T22:58:16
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CO_1038136584848889970149201
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
A
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MD_1213582242930949697188121
2024-08-16T14:59:42
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_11_875_5" ]
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2023-12-01T22:58:16
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CO_1038986417877876043194617
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
2024-08-16T14:31:59
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PO_1769062867790248027451187
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MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_interstitials_HCP2_crowdionB2_3500_8" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1043079414822753609515396
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
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MD_1213582242930949697188121
2024-08-16T15:16:55
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PO_6841548737993680318072159
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MD_8072777543375650454349539
null
[ "Re_iter0_T3500_1_mp-1186901_elastic_B222_dist03_11_32" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1043108982694029729591468
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}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
Re
A
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2024-08-16T15:16:43
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2023-12-01T22:58:16
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CO_1043629574338885286164039
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
2024-08-16T15:18:46
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MD_2333412701806194962250672
null
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2023-12-01T22:58:16
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CO_1045012839772434687586959
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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2024-08-16T14:58:17
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MD_2333412701806194962250672
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_2_3500_6" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1050798863163647353676516
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
2024-08-16T14:48:46
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MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_8_11" ]
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2023-12-01T22:58:16
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CO_1050902484173176635292876
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
2024-08-16T14:17:05
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MD_2333412701806194962250672
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_9_3500_5" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1051395460861181888681869
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}
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T14:15:01
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_9_3500_4" ]
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2023-12-01T22:58:16
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CO_1051904173866675897204660
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
Re
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MD_1213582242930949697188121
2024-08-16T14:49:57
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PO_7058194162969956114896083
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MD_3580205984756795750502668
null
[ "Re_iter1_sc_elastic_B222_dist03_0_3500_2" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1052903936017985815021569
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
A
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MD_1213582242930949697188121
2024-08-16T15:04:09
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PO_5399122735359754928429431
{"materials-project-id": "mp-1186901", "hash": "8072777543375650454349539023274221503174068012903507261477532455731713302719769878906366450635675685518876347596141677244640665411398937363872191258209873", "id": "MD_8072777543375650454349539"}
MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_10_20", "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_10_23" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1053163235870510221522984
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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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
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MD_1213582242930949697188121
2024-08-16T15:12:47
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MD_3140906615584827818889926
null
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[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1054364559728325101162447
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
Re
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MD_1213582242930949697188121
2024-08-16T15:25:36
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MD_3894327761601644436733559
null
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2023-12-01T22:58:16
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CO_1054442467256775506908549
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}
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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
2024-08-16T14:11:57
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PO_1230801624994825741102831
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MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_interstitials_HCP2_crowdionB_3500_7" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1054726015635948794451471
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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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
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T15:26:16
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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
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MD_1213582242930949697188121
2024-08-16T15:03:51
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MD_3894327761601644436733559
null
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2023-12-01T22:58:16
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CO_1058960689004559372878551
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
2024-08-16T15:31:34
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PO_2051970380497188713443799
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_dbB_3500_12" ]
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2023-12-01T22:58:16
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CO_1059632342583854891183853
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
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MD_1213582242930949697188121
2024-08-16T14:54:18
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MD_2333412701806194962250672
null
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2023-12-01T22:58:16
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CO_1059906868981951327946267
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
2024-08-16T15:19:53
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdionP_3500_4" ]
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2023-12-01T22:58:16
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CO_1060116333326652356033152
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
Re8
Re
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MD_1213582242930949697188121
2024-08-16T14:14:38
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MD_3580205984756795750502668
null
[ "Re_iter1_sc_elastic_B222_dist03_0_3500_5" ]
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2023-12-01T22:58:16
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CO_1061531756095705110385414
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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MD_1213582242930949697188121
2024-08-16T14:57:45
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2023-12-01T22:58:16
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CO_1062360393391068066676066
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
Re17
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MD_1213582242930949697188121
2024-08-16T14:15:21
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MD_3140906615584827818889926
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2023-12-01T22:58:16
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CO_1063787678704606084562552
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
Re
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MD_1213582242930949697188121
2024-08-16T14:54:27
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PO_1487251246346655125615581
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1063862714670408914010535
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
Re
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MD_1213582242930949697188121
2024-08-16T15:19:16
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PO_2340252598561315478272643
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_elastic_B222_dist03_6_10" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1063888347086225574554295
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
2024-08-16T14:27:24
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PO_5819874809807959907174558
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MD_4820518588507787498309475
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_6_875_7" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1064180154649450341976737
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
Re32
Re
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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
Re15
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MD_1213582242930949697188121
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2023-12-01T22:58:16
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CO_1064434577634561931256573
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
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MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_2_3" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1064460736935094750938614
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
Re31
Re
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:32:53
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PO_1353370898271938976345026
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MD_5276451162749980934843793
null
[ "Re_iter0_T875_3_mp-8642_vacancies_Vac_0_1" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1065698071742970599957320
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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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
A
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[ "Re" ]
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MD_1213582242930949697188121
2024-08-16T15:24:22
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PO_2908001328224666555021428
{"materials-project-id": "mp-8642", "temperature": 875, "hash": "4820518588507787498309475974572485981888251467462188826379741861055800348663208623625121292514595542784805618367869818107146036450004379793983452396383543", "id": "MD_4820518588507787498309475"}
MD_4820518588507787498309475
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_10_875_11" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1067032447841146082572375
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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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
Re15
Re
A
[ 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75 ]
[ "Re" ]
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MD_1213582242930949697188121
2024-08-16T15:30:37
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PO_1163251249520478318447241
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1067428910943721145594583
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
2024-08-16T15:23:52
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MD_1951564499902567866502008
null
[ "Re_iter2_0_mp-8_interstitials_HCP2_interTdB_875_4" ]
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2023-12-01T22:58:16
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CO_1068767865995063213793031
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
A
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MD_1213582242930949697188121
2024-08-16T14:11:58
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PO_6648502840678561032324750
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_1_875_18" ]
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2023-12-01T22:58:16
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CO_1070704483170381017277379
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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2024-08-16T15:12:47
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MD_2333412701806194962250672
null
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2023-12-01T22:58:16
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CO_1071785495744658651859112
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
2024-08-16T14:51:47
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2023-12-01T22:58:16
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CO_1074203860322348947274602
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
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:13:58
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PO_3216732992606205229534241
{"materials-project-id": "mp-8", "temperature": 3500, "hash": "3894327761601644436733559808646675100022897745511395985665381043435300799855739687517119493525052493566939130455301013067924468457095896945481109033016680", "id": "MD_3894327761601644436733559"}
MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_interstitials_HCP2_crowdionB2_3500_5" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1076035491377202243425450
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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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}
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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
2024-08-16T15:12:28
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_2_17" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1078736413537471298118206
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
A
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MD_1213582242930949697188121
2024-08-16T14:46:22
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PO_7651531125526095130951316
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MD_2333412701806194962250672
null
[ "Re_iter2_3_mp-8642_elastic_B222_dist03_6_3500_1" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1078889488720563461545064
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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[ 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
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T14:13:25
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1080149844952482347739075
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
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1080461959241945019381215
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
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T14:27:07
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_elastic_B222_dist03_8_9" ]
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2023-12-01T22:58:16
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CO_1080707562308778429119912
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
Re16
Re
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2024-08-16T15:24:06
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MD_1951564499902567866502008
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[ "Re_iter1_0_mp-8_elastic_B222_dist03_0_875_2" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1081396180144768930022529
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
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MD_1213582242930949697188121
2024-08-16T15:29:19
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MD_5276451162749980934843793
null
[ "Re_iter0_T875_3_mp-8642_vacancies_Vac_0_3" ]
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2023-12-01T22:58:16
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CO_1084107096070750794121334
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
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2024-08-16T15:10:09
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CO_1086083300663558099839214
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
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MD_1213582242930949697188121
2024-08-16T14:30:49
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1088353415552959677540947
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
2024-08-16T14:38:39
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_9_4" ]
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2023-12-01T22:58:16
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CO_1088966436179645759993035
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
2024-08-16T14:52:21
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1089653887409964500975251
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
2024-08-16T15:24:04
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2023-12-01T22:58:16
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CO_1093616024173097653342971
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
Re
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MD_1213582242930949697188121
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MD_8097482567437995173613322
null
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2023-12-01T22:58:16
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CO_1094186693525189005860391
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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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
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2023-12-01T22:58:16
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CO_1095623903905424577752240
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
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2024-08-16T15:10:08
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MD_3580205984756795750502668
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2023-12-01T22:58:16
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CO_1096196966189991096005454
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
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MD_1213582242930949697188121
2024-08-16T14:27:23
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MD_3140906615584827818889926
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[ "Re_iter0_T3500_0_mp-8_elastic_B222_dist03_2_6" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1096758695033228837928062
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
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MD_1213582242930949697188121
2024-08-16T15:18:36
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MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_6_19" ]
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2023-12-01T22:58:16
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CO_1097127575370029830801723
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
2024-08-16T14:34:00
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[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_0_7" ]
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2023-12-01T22:58:16
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CO_1099362702541689998936219
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
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T14:45:40
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MD_3140906615584827818889926
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2023-12-01T22:58:16
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CO_1100290520105704403217669
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
2024-08-16T15:07:49
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_interstitials_HCP2_db_27" ]
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2023-12-01T22:58:16
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CO_1101152709992164251570084
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
2024-08-16T14:39:55
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PO_1178710713435545347145053
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1105342461668660310829082
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
2024-08-16T14:12:12
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null
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2023-12-01T22:58:16
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CO_1105704580328748911916682
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
Re17
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MD_1213582242930949697188121
2024-08-16T14:33:39
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_interstitials_HCP2_dbP_16" ]
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2023-12-01T22:58:16
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CO_1105778647725243404013808
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
Re8
Re
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MD_1213582242930949697188121
2024-08-16T14:56:41
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_2_875_18" ]
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2023-12-01T22:58:16
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CO_1107376121124610454190157
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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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
Re8
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MD_1213582242930949697188121
2024-08-16T14:38:50
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MD_3580205984756795750502668
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2023-12-01T22:58:16
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CO_1107521731918002975256138
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
Re16
Re
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MD_1213582242930949697188121
2024-08-16T14:15:23
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_elastic_B222_dist03_0_49" ]
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2023-12-01T22:58:16
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CO_1108136078346067411159424
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