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

Dataset card Data Studio Files Community
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Re16
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2024-08-16T15:24:28
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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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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
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MD_1213582242930949697188121
2024-08-16T14:50:18
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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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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
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MD_1213582242930949697188121
2024-08-16T15:20:19
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MD_5276451162749980934843793
null
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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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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
2024-08-16T15:10:27
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MD_8097482567437995173613322
null
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2023-12-01T22:58:16
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CO_1217008929631542533539403
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
Re
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MD_1213582242930949697188121
2024-08-16T15:03:30
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MD_3580205984756795750502668
null
[ "Re_iter2_sc_elastic_B222_dist03_6_3500_8" ]
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2023-12-01T22:58:16
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CO_1217081031707138668710768
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 ] ]
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re32
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2024-08-16T14:35:05
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_11_19" ]
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2023-12-01T22:58:16
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CO_1217394133606276594007514
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
2024-08-16T15:20:21
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PO_3193488853837652615575966
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MD_4820518588507787498309475
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_8_875_3" ]
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2023-12-01T22:58:16
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CO_1218751268366404967143961
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
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2024-08-16T14:18:27
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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
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MD_1213582242930949697188121
2024-08-16T14:16:37
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2023-12-01T22:58:16
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CO_1219459816504907027358148
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
Re8
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MD_1213582242930949697188121
2024-08-16T14:19:25
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2023-12-01T22:58:16
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CO_1219529771027271300159265
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
2024-08-16T15:14:14
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MD_3140906615584827818889926
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CO_1219834283489374931728270
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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Re
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MD_1213582242930949697188121
2024-08-16T15:14:17
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1220179533696141218739034
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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MD_1213582242930949697188121
2024-08-16T15:33:22
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PO_1191995324883553910624023
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1221066970035638730356396
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
Re17
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MD_1213582242930949697188121
2024-08-16T15:05:41
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PO_5949029128757835878541256
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_dbPP_875_13" ]
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2023-12-01T22:58:16
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CO_1221203509459508259683994
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
Re31
Re
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MD_1213582242930949697188121
2024-08-16T15:33:30
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PO_1192739223692167737244259
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MD_4820518588507787498309475
null
[ "Re_iter2_3_mp-8642_vacancies_Vac_0_875_6" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1221531133062141321765233
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
2024-08-16T15:04:08
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PO_5432645190480456360924125
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_5_7", "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_5_14" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1222330492996551559465383
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
Re16
Re
A
[ 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75 ]
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2024-08-16T15:13:24
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2023-12-01T22:58:16
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CO_1222709525025237513500172
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
2024-08-16T14:15:15
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1228950224914447509777278
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
2024-08-16T14:38:00
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MD_8097482567437995173613322
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2023-12-01T22:58:16
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CO_1229763334941418572215784
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
2024-08-16T14:13:46
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_elastic_B222_dist03_2_47" ]
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2023-12-01T22:58:16
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CO_1230474018044376657410529
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
2024-08-16T14:17:49
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdionB_875_7" ]
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2023-12-01T22:58:16
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CO_1230661193758379442519227
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
2024-08-16T14:16:48
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdionB2_875_9" ]
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2023-12-01T22:58:16
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CO_1231882752303960005412340
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
Re16
Re
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MD_1213582242930949697188121
2024-08-16T15:03:28
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PO_1178053646026673466747056
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MD_1951564499902567866502008
null
[ "Re_iter2_0_mp-8_elastic_B222_dist03_3_875_9" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1232514828612976011996894
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
2024-08-16T14:39:46
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2023-12-01T22:58:16
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CO_1232921047051511656497979
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
2024-08-16T14:59:51
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MD_1951564499902567866502008
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2023-12-01T22:58:16
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CO_1233046711955332202827653
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
2024-08-16T15:22:10
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_interOh_3500_8" ]
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2023-12-01T22:58:16
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CO_1234796866441202295667027
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}
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
2024-08-16T14:37:13
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MD_3580205984756795750502668
null
[ "Re_iter1_sc_elastic_B222_dist03_7_3500_10" ]
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2023-12-01T22:58:16
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CO_1235591826972682868064308
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
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T15:34:23
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PO_1315566143629171569073423
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_6_3500_6" ]
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2023-12-01T22:58:16
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CO_1235605325049973213396429
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
A
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MD_1213582242930949697188121
2024-08-16T14:18:18
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_interstitials_HCP2_dbP2_2", "Re_iter0_T875_0_mp-8_interstitials_HCP2_dbP2_5", "Re_iter0_T875_0_mp-8_interstitials_HCP2_dbP2_12" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1235894337458922644516124
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 ] ]
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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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[ "Re" ]
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1
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2024-08-16T15:35:04
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1236150568214761978624872
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
2024-08-16T15:31:07
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1236900295882610352407004
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
2024-08-16T14:12:49
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PO_3126419468733758564525797
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1237312344652571235098457
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
Re8
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
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MD_1213582242930949697188121
2024-08-16T14:18:12
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2023-12-01T22:58:16
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CO_1238638451902277462642997
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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CO_1238807965218369506622729
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
2024-08-16T15:15:11
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MD_3140906615584827818889926
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2023-12-01T22:58:16
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CO_1238897204004594060786602
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
Re11
Re
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MD_1213582242930949697188121
2024-08-16T15:26:13
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PO_2828095403052188561880004
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MD_1115727940513345059617207
null
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2023-12-01T22:58:16
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CO_1239287235272994297149031
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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MD_1213582242930949697188121
2024-08-16T15:17:39
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PO_2878379103168032060753091
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MD_1951564499902567866502008
null
[ "Re_iter2_0_mp-8_elastic_B222_dist03_5_875_9" ]
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2023-12-01T22:58:16
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CO_1239669284995947296970231
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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2024-08-16T15:02:05
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2023-12-01T22:58:16
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CO_1239758484528956923786389
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
2024-08-16T15:00:25
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_interTd_875_9" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1240211728690453381892916
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
Re32
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MD_1213582242930949697188121
2024-08-16T14:16:36
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MD_4820518588507787498309475
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_8_875_2" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1241117289617545942128517
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
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MD_1213582242930949697188121
2024-08-16T15:38:55
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2023-12-01T22:58:16
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CO_1242335921750225926677141
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
2024-08-16T14:35:53
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MD_3894327761601644436733559
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[ "Re_iter1_0_mp-8_interstitials_HCP2_interTdB_3500_9" ]
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2023-12-01T22:58:16
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CO_1242951678737270420771336
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
Re8
Re
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MD_1213582242930949697188121
2024-08-16T14:12:47
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MD_3580205984756795750502668
null
[ "Re_iter1_sc_elastic_B222_dist03_1_3500_19" ]
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2023-12-01T22:58:16
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CO_1244932022007736150065108
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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2024-08-16T15:22:22
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CO_1245683762124357119004085
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
2024-08-16T14:32:21
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MD_3894327761601644436733559
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2023-12-01T22:58:16
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CO_1246261306271022849654883
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
2024-08-16T15:31:51
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PO_6242972133378394319101766
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdion_875_18" ]
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2023-12-01T22:58:16
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CO_1246456529000795791803374
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
Re17
Re
A
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MD_1213582242930949697188121
2024-08-16T15:10:28
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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
2024-08-16T15:19:22
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MD_8097482567437995173613322
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2023-12-01T22:58:16
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CO_1249427988549199035044951
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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Re
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MD_1213582242930949697188121
2024-08-16T14:38:42
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MD_3580205984756795750502668
null
[ "Re_iter2_sc_elastic_B222_dist03_11_3500_7" ]
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2023-12-01T22:58:16
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CO_1249592594526798897333557
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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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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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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2023-12-01T22:58:16
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CO_1251049597322186557703245
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
2024-08-16T14:29:56
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdionP_875_12" ]
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2023-12-01T22:58:16
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CO_1251178698681146664023284
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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MD_1213582242930949697188121
2024-08-16T15:21:59
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PO_1165258031261790683653586
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MD_3894327761601644436733559
null
[ "Re_iter2_0_mp-8_elastic_B222_dist03_2_3500_1" ]
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2023-12-01T22:58:16
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CO_1251924409603903348370389
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
A
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MD_1213582242930949697188121
2024-08-16T15:26:31
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PO_1098006534156604741950090
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MD_3580205984756795750502668
null
[ "Re_iter1_sc_elastic_B222_dist03_9_3500_0" ]
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2023-12-01T22:58:16
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CO_1252121722184565892149368
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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
A
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MD_1213582242930949697188121
2024-08-16T15:15:46
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PO_4782281601772522920904999
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_7_875_11" ]
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2023-12-01T22:58:16
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CO_1253291900015466682484202
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 ] ]
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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
Re11
Re
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MD_1213582242930949697188121
2024-08-16T14:48:32
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PO_5521741699763283925085663
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MD_2380450930435309551362266
null
[ "Re_iter2_1_mp-1186901_vacancies_Vac_0_875_1" ]
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2023-12-01T22:58:16
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CO_1253730343145725450149879
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
Re8
Re
A
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VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T14:35:58
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MD_8097482567437995173613322
null
[ "Re_iter2_sc_elastic_B222_dist03_7_875_3" ]
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2023-12-01T22:58:16
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CO_1256466242430816433022904
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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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:35:45
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PO_1802871862905539120379263
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_interstitials_HCP2_interOh_9" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1257514528638717668336475
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
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MD_1213582242930949697188121
2024-08-16T14:45:21
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MD_4820518588507787498309475
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2023-12-01T22:58:16
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CO_1259397738608332598436240
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
2024-08-16T14:52:06
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PO_1285011891870527416082546
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_4_11" ]
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2023-12-01T22:58:16
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CO_1259718778997819688250081
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
Re8
Re
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MD_1213582242930949697188121
2024-08-16T14:39:13
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PO_1339526641282779898915479
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MD_8097482567437995173613322
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2023-12-01T22:58:16
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CO_1260039418350514845647504
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
A
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MD_1213582242930949697188121
2024-08-16T15:25:55
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null
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2023-12-01T22:58:16
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CO_1262188873834821495550782
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
2024-08-16T14:11:57
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MD_4820518588507787498309475
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2023-12-01T22:58:16
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CO_1264271332622551205282145
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
2024-08-16T15:02:44
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2023-12-01T22:58:16
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CO_1265697811397831888323020
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
2024-08-16T14:14:04
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PO_1443975666017913371445741
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_elastic_B222_dist03_8_3500_5" ]
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2023-12-01T22:58:16
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CO_1266714656644930536087637
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
2024-08-16T14:47:38
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PO_4775803263125745020256093
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MD_2333412701806194962250672
null
[ "Re_iter2_3_mp-8642_elastic_B222_dist03_8_3500_5" ]
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2023-12-01T22:58:16
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CO_1268362028679756372164868
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
Re8
Re
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2024-08-16T15:15:02
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2023-12-01T22:58:16
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CO_1269323807375889218841724
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
2024-08-16T14:44:55
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MD_1951564499902567866502008
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdionB2_875_5" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1271573672854095481795150
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
2024-08-16T15:01:42
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MD_5276451162749980934843793
null
[ "Re_iter0_T3500_3_mp-8642_elastic_B222_dist03_5_2" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1271825484769792453593202
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
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:52:51
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2023-12-01T22:58:16
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CO_1272146451740639634687002
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
2024-08-16T14:56:45
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MD_1951564499902567866502008
null
[ "Re_iter2_0_mp-8_interstitials_HCP2_crowdion_875_8" ]
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2023-12-01T22:58:16
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CO_1272466988986149095547645
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
2024-08-16T14:14:56
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PO_5401292228613027740672146
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MD_3140906615584827818889926
null
[ "Re_iter0_T875_0_mp-8_interstitials_HCP2_interOh_13" ]
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2023-12-01T22:58:16
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CO_1272898737650073845894017
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
Re17
Re
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MD_1213582242930949697188121
2024-08-16T14:34:48
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MD_3894327761601644436733559
null
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2023-12-01T22:58:16
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CO_1275070463527139057843996
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
2024-08-16T14:30:01
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MD_3894327761601644436733559
null
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2023-12-01T22:58:16
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CO_1277557401853628581732778
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
A
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MD_1213582242930949697188121
2024-08-16T14:51:41
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PO_7442096565428693568534761
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_dbP2_3500_4" ]
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2023-12-01T22:58:16
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CO_1282447187699796689026071
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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MD_1213582242930949697188121
2024-08-16T14:39:29
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MD_2333412701806194962250672
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_5_3500_5" ]
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2023-12-01T22:58:16
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CO_1282565898199592526772503
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
2024-08-16T14:49:24
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MD_4820518588507787498309475
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2023-12-01T22:58:16
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CO_1284922472200279576904563
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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2024-08-16T14:34:43
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[ "Re_iter0_T875_3_mp-8642_elastic_B222_dist03_8_9", "Re_iter0_T875_3_mp-8642_elastic_B222_dist03_8_18" ]
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2023-12-01T22:58:16
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CO_1285487242239785021883341
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
2024-08-16T14:59:21
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MD_3140906615584827818889926
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2023-12-01T22:58:16
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CO_1286125284193687869037084
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
2024-08-16T15:24:57
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MD_3140906615584827818889926
null
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2023-12-01T22:58:16
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CO_1286906400388239056590221
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
2024-08-16T15:13:55
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_crowdionB2_3500_8" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1287066652783089295997494
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
2024-08-16T14:13:26
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MD_8072777543375650454349539
null
[ "Re_iter0_T3500_1_mp-1186901_elastic_B222_dist03_4_9" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1287296159044713212523046
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
A
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MD_1213582242930949697188121
2024-08-16T14:57:21
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PO_7477053296696739505392714
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MD_3580205984756795750502668
null
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2023-12-01T22:58:16
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CO_1288275623238514339591711
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
Re16
Re
A
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MD_1213582242930949697188121
2024-08-16T15:01:13
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PO_9953344625479777873191134
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_elastic_B222_dist03_3_10" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1288418902601377689694304
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
2024-08-16T14:12:10
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PO_8069101170934163530554777
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MD_8072777543375650454349539
null
[ "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_9_34", "Re_iter0_T875_1_mp-1186901_elastic_B222_dist03_9_40" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1288599660878186304950499
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
2024-08-16T14:56:47
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PO_3300107973328351475666700
{"materials-project-id": "mp-8", "hash": "3140906615584827818889926028981497781902602918718492657795198645954064294979943651666995033116565051856223247969969595453682419614342884875296122884881308", "id": "MD_3140906615584827818889926"}
MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_interstitials_HCP2_dbB_15" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1289220164468965202955163
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
2024-08-16T14:48:42
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MD_3140906615584827818889926
null
[ "Re_iter0_T3500_0_mp-8_elastic_B222_dist03_3_14" ]
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2023-12-01T22:58:16
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CO_1289220851319895393596905
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
2024-08-16T14:35:44
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PO_3777022980263217548732222
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MD_8072777543375650454349539
null
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2023-12-01T22:58:16
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CO_1289712956617491425322711
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_4820518588507787498309475
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_10_875_4" ]
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2023-12-01T22:58:16
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CO_1289852812118850455537307
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
2024-08-16T14:13:58
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MD_2333412701806194962250672
null
[ "Re_iter1_3_mp-8642_elastic_B222_dist03_2_3500_9" ]
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2023-12-01T22:58:16
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CO_1290332003903924295864714
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
2024-08-16T14:12:53
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PO_1065662955463581913364274
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MD_1951564499902567866502008
null
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2023-12-01T22:58:16
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CO_1290437757784255236829744
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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2024-08-16T15:28:32
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CO_1290817079567065011175634
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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2024-08-16T14:42:12
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2023-12-01T22:58:16
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CO_1291442206509553580974864
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
2024-08-16T15:10:41
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PO_5743668898532850420398997
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MD_1951564499902567866502008
null
[ "Re_iter2_0_mp-8_interstitials_HCP2_crowdionP_875_0" ]
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2023-12-01T22:58:16
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CO_1291949988362246056867867
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
2024-08-16T14:38:09
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PO_3149396778042151894498620
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_10_875_14" ]
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2023-12-01T22:58:16
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CO_1292710312999077444698211
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
A
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MD_1213582242930949697188121
2024-08-16T15:31:03
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PO_7692479683359186183850770
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MD_3894327761601644436733559
null
[ "Re_iter1_0_mp-8_interstitials_HCP2_interTd_3500_7" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1292796560553871105999691
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}
10.60732/1e0997f8
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DS_gzbvdicu231p_0
23-Single-Element-DNPs_RSCDD_2023-Re__Andolina-Saidi__DS_gzbvdicu231p_0
Re8
Re
A
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:36:10
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PO_2573017850624510020465474
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MD_8097482567437995173613322
null
[ "Re_iter1_sc_elastic_B222_dist03_7_875_17" ]
[ "DS_gzbvdicu231p_0" ]
2023-12-01T22:58:16
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CO_1293868005705882209247019
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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[ 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