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

Dataset card Data Studio Files
xet
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CO_6562810589919766203361617
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:49:29
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PO_1118648219611662389257533
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_6577254158662068406128594
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:37:24
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PO_6522471308667802470544471
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MD_8723377259784243212242054
null
[ "Sb_iter2_6_mp-7761_elastic_B222_dist03_11_930_6" ]
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2023-12-01T22:58:32
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CO_6607445668465817252057184
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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VASP
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MD_1213582242930949697188121
2024-08-16T14:43:21
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PO_4707165927458488374820342
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MD_9890234894463978372076872
null
[ "Sb_iter2_2_mp-133_elastic_B222_dist03_10_232_18" ]
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2023-12-01T22:58:32
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CO_6621260856236604302668262
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:41:53
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PO_6150124663134797829576842
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MD_8723377259784243212242054
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2023-12-01T22:58:32
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CO_6625760259006754140159830
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:23:06
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PO_9139638391216400066352849
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2023-12-01T22:58:32
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CO_6628700913072947742909285
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:19:39
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PO_7679333820191186096829134
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MD_1226566192249423389047690
null
[ "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_7_9", "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_9_1", "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_11_2", "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_5_5" ]
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2023-12-01T22:58:32
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CO_6664295358968740509641520
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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CO_6664295358968740509641520
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_6664295358968740509641520
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
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CO_6664295358968740509641520
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:28:43
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PO_2667293743030921551179237
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MD_1271418612909851697008258
null
[ "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_8_5" ]
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2023-12-01T22:58:32
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CO_6667616431457367315892862
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:31:32
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PO_7605596662710515171373334
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MD_1175204308310345149590984
null
[ "Sb_iter0_T232_0_mp-104_elastic_B222_dist03_7_0", "Sb_iter0_T232_0_mp-104_elastic_B222_dist03_7_19" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_6673240210314107345410951
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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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MD_1213582242930949697188121
2024-08-16T14:25:46
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_6675608728765558708984924
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:27:18
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PO_1306121075968220181274351
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_6690574034256121994892139
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:41:18
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PO_5856675043221201926361903
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MD_1226566192249423389047690
null
[ "Sb_iter0_T232_1_mp-1179605_elastic_B222_dist03_1_16" ]
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2023-12-01T22:58:32
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CO_6701184009709961664244947
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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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MD_1213582242930949697188121
2024-08-16T14:44:34
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PO_6304085109306822685230969
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MD_9890234894463978372076872
null
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2023-12-01T22:58:31
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CO_6735204374374371646329045
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:51:26
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MD_1271418612909851697008258
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[ "Sb_iter0_T930_11_mp-10630_elastic_B222_dist03_2_3" ]
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2023-12-01T22:58:32
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CO_6739076443030582959264621
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:38:13
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MD_2164565307674838913500201
null
[ "Sb_iter0_T930_6_mp-7761_elastic_B222_dist03_10_1" ]
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2023-12-01T22:58:32
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CO_6743391356019643730781046
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:56:22
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_6749597859647128251807369
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:14:24
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2023-12-01T22:58:32
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CO_6750844676800484980368173
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:59:13
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PO_3351103426560754264218569
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MD_5600237606314913062759184
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2023-12-01T22:58:32
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CO_6754041408360621894921135
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:06:32
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PO_1215555698489829591277406
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_6755372521300611238751576
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:10:55
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PO_7432291255662381755917507
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MD_3072275598411872336810647
null
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2023-12-01T22:58:32
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CO_6769588629788263547410182
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:43:54
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MD_1226566192249423389047690
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2023-12-01T22:58:32
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CO_6793320162358218080650631
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:30:06
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PO_3348324710774830320490570
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MD_1271418612909851697008258
null
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2023-12-01T22:58:32
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CO_6814437203542481490882048
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:27:40
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MD_1271418612909851697008258
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2023-12-01T22:58:32
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CO_6815248944891409166531932
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:29:32
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PO_4471961571640310010611985
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MD_1531921544206064124007380
null
[ "Sb_iter0_T232_2_mp-133_elastic_B222_dist03_11_2", "Sb_iter0_T232_2_mp-133_elastic_B222_dist03_5_0", "Sb_iter0_T232_2_mp-133_elastic_B222_dist03_7_3", "Sb_iter0_T232_2_mp-133_elastic_B222_dist03_9_17" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_6820509512283545733999396
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:24:03
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MD_1271418612909851697008258
null
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2023-12-01T22:58:31
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CO_6840744324029049141602224
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb16
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MD_1213582242930949697188121
2024-08-16T14:40:07
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PO_9025881069089877549170776
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_6892682636201018049113537
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
[ [ 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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:40:40
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PO_1003179791332543338144494
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MD_8723377259784243212242054
null
[ "Sb_iter1_6_mp-7761_elastic_B222_dist03_10_930_0" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:31
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CO_6935830070358696826711306
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Sb" ]
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2023-12-01T17:58:46
[ [ 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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:35:38
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MD_1531921544206064124007380
null
[ "Sb_iter0_T232_2_mp-133_7" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_6979507254625294052246239
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb16
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VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:13:11
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PO_3025619312090681829053095
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MD_2164565307674838913500201
null
[ "Sb_iter0_T232_6_mp-7761_elastic_B222_dist03_6_19" ]
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2023-12-01T22:58:31
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CO_6993562899798985865093582
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Sb" ]
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5,529
0
5,529
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3,545.21839
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2023-12-01T17:58:46
[ [ 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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb
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MD_1213582242930949697188121
2024-08-16T15:14:31
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PO_1022303320696918213681528
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MD_1531921544206064124007380
null
[ "Sb_iter0_T930_2_mp-133_17" ]
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2023-12-01T22:58:31
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CO_7042134600306610362430960
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Sb" ]
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2023-12-01T17:58:46
[ [ 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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb16
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CO_7063974249277418222905006
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:52:02
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CO_7063974249277418222905006
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:52:02
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MD_1226566192249423389047690
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[ "Sb_iter0_T232_1_mp-1179605_elastic_B222_dist03_7_5", "Sb_iter0_T232_1_mp-1179605_elastic_B222_dist03_9_11", "Sb_iter0_T232_1_mp-1179605_elastic_B222_dist03_11_17", "Sb_iter0_T232_1_mp-1179605_elastic_B222_dist03_5_11" ]
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2023-12-01T22:58:31
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CO_7063974249277418222905006
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:52:02
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MD_1226566192249423389047690
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2023-12-01T22:58:31
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CO_7063974249277418222905006
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:20:35
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MD_1531921544206064124007380
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2023-12-01T22:58:32
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CO_7083570220986791245286824
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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MD_1213582242930949697188121
2024-08-16T15:20:35
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2023-12-01T22:58:32
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CO_7083570220986791245286824
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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MD_1213582242930949697188121
2024-08-16T15:20:35
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PO_5261291760971909636545646
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MD_1531921544206064124007380
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[ "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_7_17", "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_9_12", "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_11_1", "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_5_14" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_7083570220986791245286824
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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2024-08-16T15:20:35
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CO_7083570220986791245286824
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:45:12
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2023-12-01T22:58:32
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CO_7102445604691801211549088
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:14:31
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PO_1386693528687495552824619
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MD_3072275598411872336810647
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2023-12-01T22:58:32
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CO_7108529974282840762719872
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:56:23
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PO_1070494430253295643897665
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MD_6774213934135675701540773
null
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2023-12-01T22:58:32
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CO_7140003990579937403402439
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:39:19
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PO_1466475414027585737210173
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MD_1175204308310345149590984
null
[ "Sb_iter0_T930_0_mp-104_elastic_B222_dist03_6_17" ]
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2023-12-01T22:58:32
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CO_7161460674070673965804055
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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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MD_1213582242930949697188121
2024-08-16T15:16:01
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PO_9193305982234358115646955
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MD_1069713809891562784388190
null
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2023-12-01T22:58:32
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CO_7192044488236527927714715
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:03:45
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PO_6028415267344227385878103
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MD_3072275598411872336810647
null
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2023-12-01T22:58:32
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CO_7196069746386298111456550
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:53:30
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PO_4523049376573406411534925
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MD_9890234894463978372076872
null
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2023-12-01T22:58:32
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CO_7229913523257978906464240
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:59:41
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MD_2164565307674838913500201
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2023-12-01T22:58:32
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CO_7238557626442945396676912
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:08:54
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PO_5299192721502240026208612
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2023-12-01T22:58:32
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CO_7243844472566282814463460
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:24:11
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PO_1217300898305774575661417
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MD_6774213934135675701540773
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2023-12-01T22:58:32
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CO_7245255179378763296384120
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:32:40
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MD_3072275598411872336810647
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2023-12-01T22:58:32
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CO_7268206982799402293227547
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:24:38
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MD_1531921544206064124007380
null
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2023-12-01T22:58:32
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CO_7278892626533457496625041
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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GPL-3.0-only
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:24:38
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MD_1531921544206064124007380
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2023-12-01T22:58:32
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CO_7278892626533457496625041
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Sb" ]
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2023-12-01T17:58:46
[ [ 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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb
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MD_1213582242930949697188121
2024-08-16T14:56:16
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MD_1271418612909851697008258
null
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2023-12-01T22:58:31
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CO_7285581628299637558120033
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:52:06
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2023-12-01T22:58:32
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CO_7316350927139238536914046
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:16:56
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PO_6238165452178819272396970
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MD_1271418612909851697008258
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[ "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_7_12", "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_9_15", "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_11_6", "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_5_6" ]
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2023-12-01T22:58:32
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CO_7371119097267429536878718
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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2024-08-16T14:16:56
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2023-12-01T22:58:32
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CO_7371119097267429536878718
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:16:56
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[ "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_7_12", "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_9_15", "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_11_6", "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_5_6" ]
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2023-12-01T22:58:32
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CO_7371119097267429536878718
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:16:56
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2023-12-01T22:58:32
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CO_7371119097267429536878718
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:08:07
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PO_1142991224741337535062481
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MD_1069713809891562784388190
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2023-12-01T22:58:32
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CO_7404171304007332387585021
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:21:24
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MD_1175204308310345149590984
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2023-12-01T22:58:32
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CO_7404247952619403132921370
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:51:51
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_7424272806077741906182587
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:16:03
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PO_4757888319838561973458851
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_7442329293903032517747396
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:34:00
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MD_6196355602623336221701784
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2023-12-01T22:58:32
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CO_7453482324293040362060145
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:30:50
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MD_6196355602623336221701784
null
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2023-12-01T22:58:32
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CO_7466601179091085471836001
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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MD_1213582242930949697188121
2024-08-16T15:18:42
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CO_7534128018969719830041666
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:14:04
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PO_8042203634929137490379403
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_7554133626813175716749239
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:42:31
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PO_1300128740598534979302959
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MD_1271418612909851697008258
null
[ "Sb_iter0_T930_11_mp-10630_elastic_B222_dist03_1_18" ]
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2023-12-01T22:58:32
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CO_7593517335961639975001946
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:37:18
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MD_1531921544206064124007380
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2023-12-01T22:58:31
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CO_7613639981248177890080565
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:02:30
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PO_4502668451884228344804968
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MD_3072275598411872336810647
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2023-12-01T22:58:32
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CO_7626863671670006478203674
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:34:56
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PO_1098474367976107178147789
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MD_1531921544206064124007380
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2023-12-01T22:58:32
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CO_7639266060797905519145747
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:04:22
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2023-12-01T22:58:32
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CO_7641548095815538124862540
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:19:02
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MD_1069713809891562784388190
null
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2023-12-01T22:58:32
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CO_7670624220015519973547050
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:19:20
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PO_4952965286568278323085535
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MD_8723377259784243212242054
null
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2023-12-01T22:58:32
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CO_7676442187511013562579926
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:28:09
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_7677617744240739221244530
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
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DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:04:35
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PO_6420074042200203347297548
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MD_5600237606314913062759184
null
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2023-12-01T22:58:31
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CO_7693819469438758651070751
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:48:50
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MD_1271418612909851697008258
null
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2023-12-01T22:58:32
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CO_7697709808039975964827548
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:11:50
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MD_1175204308310345149590984
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2023-12-01T22:58:32
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CO_7707934186255408149107712
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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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MD_1213582242930949697188121
2024-08-16T15:20:47
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MD_9890234894463978372076872
null
[ "Sb_iter2_2_mp-133_elastic_B222_dist03_7_232_2" ]
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2023-12-01T22:58:32
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CO_7709068281782001714158924
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:58:39
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PO_1142305704075454804599729
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MD_1271418612909851697008258
null
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2023-12-01T22:58:31
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CO_7737444225297288364161534
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:31:48
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_7747682337349928230840400
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:30:24
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PO_4585817882007449471018161
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MD_1531921544206064124007380
null
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2023-12-01T22:58:32
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CO_7750109654174429284186020
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Sb16
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MD_1213582242930949697188121
2024-08-16T14:21:04
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PO_9542410321233904669216849
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MD_1226566192249423389047690
null
[ "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_6_13" ]
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2023-12-01T22:58:32
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CO_7750716363165707314266333
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
[ [ 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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:55:34
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PO_1164417879077022073724280
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MD_1329574950964754993516039
null
[ "Sb_iter1_2_mp-133_elastic_B222_dist03_10_930_2" ]
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2023-12-01T22:58:31
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CO_7786461430708131752278726
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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}
10.60732/7980ece8
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:51:19
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PO_1322268650298964623279650
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MD_1329574950964754993516039
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2023-12-01T22:58:32
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CO_7835579417944746001719176
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:04:40
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MD_6196355602623336221701784
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2023-12-01T22:58:32
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CO_7836578994891844158054323
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:04:29
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PO_6369051783654153718685768
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MD_6774213934135675701540773
null
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2023-12-01T22:58:32
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CO_7840016486685256469920073
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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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2023-12-01T22:58:31
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CO_7859814383542870452806307
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:43:54
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2023-12-01T22:58:32
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CO_7868460456583324564600486
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:28:38
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MD_1175204308310345149590984
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23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:10:20
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MD_5600237606314913062759184
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2023-12-01T22:58:32
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CO_7950071482183659824726598
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:38:26
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PO_1074761546265016102904794
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_7987344614374053996977847
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
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2024-08-16T14:36:30
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PO_1437984464171786852808363
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2023-12-01T22:58:32
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CO_8033357626661725891937626
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:12:24
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2023-12-01T22:58:32
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CO_8045136337440684230912255
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:42:23
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PO_6982271227706833915777553
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MD_1226566192249423389047690
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2023-12-01T22:58:32
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CO_8068461823086331683521419
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:12:44
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MD_5600237606314913062759184
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2023-12-01T22:58:32
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CO_8101737050282123882703862
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:42:11
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PO_6280043722229491774433065
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_8102619827742436067490077
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T15:24:01
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PO_5603665871926181141628801
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MD_1226566192249423389047690
null
[ "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_10_13" ]
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2023-12-01T22:58:32
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CO_8201782760398507970595386
23-Single-Element-DNPs_RSCDD_2023-Sb
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Sb from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:46
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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_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0