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

Dataset card Data Studio Files
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2023-12-01T22:58:32
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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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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
2024-08-16T14:43:46
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MD_8723377259784243212242054
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2023-12-01T22:58:32
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CO_8269197602005221827857397
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
2024-08-16T14:58:46
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MD_1175204308310345149590984
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2023-12-01T22:58:32
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CO_8358796309731466206983745
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
2024-08-16T14:20:20
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_8387213085537668175540071
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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2024-08-16T15:30:23
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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
2024-08-16T14:30:56
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2023-12-01T22:58:32
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CO_8425079818636546792313771
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
2024-08-16T14:47:02
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MD_1226566192249423389047690
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2023-12-01T22:58:32
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CO_8459514195813946104886052
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
2024-08-16T14:31:48
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PO_4651545923034912340548014
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_8495070399621135399374398
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
2024-08-16T14:27:17
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PO_5586370142015220580769042
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MD_9890234894463978372076872
null
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2023-12-01T22:58:32
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CO_8503814587257339903097024
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
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:49:34
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PO_1073510475220046197217332
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MD_3072275598411872336810647
null
[ "Sb_iter1_11_mp-10630_elastic_B222_dist03_4_930_5" ]
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2023-12-01T22:58:32
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CO_8542158956553269127633675
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
Sb48
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MD_1213582242930949697188121
2024-08-16T14:59:11
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PO_1261792631826206697935569
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MD_1175204308310345149590984
null
[ "Sb_iter0_T930_0_mp-104_elastic_B222_dist03_9_21", "Sb_iter0_T930_0_mp-104_elastic_B222_dist03_9_38" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_8560105108279383245175363
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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122,289
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0
5,529
-70.085254
3,545.21839
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2023-12-01T17:58:46
[ [ 1, 1, 1 ] ]
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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
Sb47
Sb
A
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[ "Sb" ]
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MD_1213582242930949697188121
2024-08-16T14:34:21
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PO_9820810640289677042125842
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MD_1175204308310345149590984
null
[ "Sb_iter0_T930_0_mp-104_vacancies_Vac_0_97", "Sb_iter0_T930_0_mp-104_vacancies_Vac_0_144" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_8562818788210201508467021
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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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
Sb48
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MD_1213582242930949697188121
2024-08-16T14:48:17
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PO_8329307145751590043139430
{"materials-project-id": "mp-104", "hash": "11752043083103451495909840591415926271491867612943291451032315583459774104304576606643951090635384335932466416246553743575172220382421067388474766997317180", "id": "MD_1175204308310345149590984"}
MD_1175204308310345149590984
null
[ "Sb_iter0_T232_0_mp-104_elastic_B222_dist03_3_3" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_8565080642145508350039670
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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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7980ece8
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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
2024-08-16T14:26:04
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PO_5870910729025959195378274
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_8584343477561737812421907
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
2024-08-16T15:40:40
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MD_6196355602623336221701784
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2023-12-01T22:58:32
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CO_8596909689435937262532921
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
2024-08-16T15:10:10
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MD_1226566192249423389047690
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2023-12-01T22:58:32
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CO_8599712696067853801191052
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
2024-08-16T15:36:50
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MD_1271418612909851697008258
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2023-12-01T22:58:32
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CO_8613774370948272048775278
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
2024-08-16T15:41:21
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MD_6774213934135675701540773
null
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2023-12-01T22:58:32
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CO_8673234234455991031164886
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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MD_1213582242930949697188121
2024-08-16T15:27:37
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MD_1271418612909851697008258
null
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2023-12-01T22:58:32
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CO_8693352945135406505539174
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
2024-08-16T14:43:34
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PO_8182081474370571251509201
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MD_9890234894463978372076872
null
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2023-12-01T22:58:32
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CO_8731746987583130206433343
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
2024-08-16T14:30:16
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PO_3483685531460103133552677
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MD_6196355602623336221701784
null
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2023-12-01T22:58:32
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CO_8769035919374418652236983
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
2024-08-16T14:44:51
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PO_1281998699532867707365034
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MD_8723377259784243212242054
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2023-12-01T22:58:32
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CO_8814084665285934274065508
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
2024-08-16T15:10:21
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PO_5550213535939272552547303
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MD_9890234894463978372076872
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2023-12-01T22:58:32
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CO_8822120919140691060494862
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
2024-08-16T14:55:58
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PO_7778595075293216583861622
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MD_1531921544206064124007380
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2023-12-01T22:58:32
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CO_8832465506559159432773559
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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2024-08-16T15:04:25
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MD_1175204308310345149590984
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CO_8841303444087737047353094
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
2024-08-16T14:52:52
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MD_1069713809891562784388190
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2023-12-01T22:58:32
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CO_8865213055995594957597925
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
2024-08-16T14:21:17
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PO_5596992941377383764612742
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MD_6774213934135675701540773
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2023-12-01T22:58:32
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CO_8874305440321642852463977
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
2024-08-16T14:50:59
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2023-12-01T22:58:32
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CO_8908171088207541942633038
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
2024-08-16T14:46:51
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PO_1338063408356799605580702
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_8915937644671194863441510
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
2024-08-16T14:27:40
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MD_1175204308310345149590984
null
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2023-12-01T22:58:32
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CO_8983783011295664980879282
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
2024-08-16T15:22:44
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PO_2056063429194165209085891
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_9013573221010288108949574
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
2024-08-16T14:30:57
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PO_6286039871919319538964853
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MD_1175204308310345149590984
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2023-12-01T22:58:32
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CO_9035154953407717772793867
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
2024-08-16T14:51:36
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PO_3074250551681673061253894
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MD_1329574950964754993516039
null
[ "Sb_iter2_2_mp-133_elastic_B222_dist03_2_930_6" ]
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2023-12-01T22:58:32
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CO_9041786176019097409835052
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
Sb32
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MD_1213582242930949697188121
2024-08-16T14:29:30
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PO_9038307183190011130017151
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MD_1271418612909851697008258
null
[ "Sb_iter0_T232_11_mp-10630_elastic_B222_dist03_3_0" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_9051023466803690756596725
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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MD_1213582242930949697188121
2024-08-16T14:58:55
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_9063405976615880674510880
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
2024-08-16T15:26:51
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MD_3072275598411872336810647
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2023-12-01T22:58:32
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CO_9081447849145131417630211
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
2024-08-16T14:49:01
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PO_1980585891497992397436048
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MD_9890234894463978372076872
null
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2023-12-01T22:58:32
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CO_9130000224189480537080057
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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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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2024-08-16T15:23:34
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2023-12-01T22:58:32
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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
2024-08-16T15:38:31
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PO_1180460278726905271669886
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2023-12-01T22:58:32
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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
2024-08-16T15:41:09
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MD_1175204308310345149590984
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2023-12-01T22:58:32
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CO_9172662999169019071782111
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
2024-08-16T15:15:37
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MD_1069713809891562784388190
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2023-12-01T22:58:32
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CO_9190256035902316691198530
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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[ "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_9198492749215189399096753
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_9198492749215189399096753
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
2024-08-16T15:07:30
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PO_4297615803043840535564256
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MD_1175204308310345149590984
null
[ "Sb_iter0_T930_0_mp-104_elastic_B222_dist03_3_9" ]
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2023-12-01T22:58:32
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CO_9207361962406023406462710
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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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7980ece8
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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
2024-08-16T14:56:00
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PO_7824821600678381302284949
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MD_1271418612909851697008258
null
[ "Sb_iter0_T232_11_mp-10630_17" ]
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2023-12-01T22:58:31
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CO_9208176067570479420480585
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
2024-08-16T14:59:58
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PO_1070254871698856618593679
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MD_2164565307674838913500201
null
[ "Sb_iter0_T930_6_mp-7761_interstitials_BCC2_interTd_18" ]
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2023-12-01T22:58:32
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CO_9228082093454021045603157
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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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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DS_z90lfjg88fzo_0
23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
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MD_1213582242930949697188121
2024-08-16T14:26:45
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PO_1129935256380385269727326
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MD_1329574950964754993516039
null
[ "Sb_iter2_2_mp-133_elastic_B222_dist03_0_930_6" ]
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2023-12-01T22:58:32
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CO_9240535459796068583309385
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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[ 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
Sb32
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MD_1213582242930949697188121
2024-08-16T15:13:09
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PO_1097359444162339799977422
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MD_6196355602623336221701784
null
[ "Sb_iter2_11_mp-10630_elastic_B222_dist03_11_232_2" ]
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2023-12-01T22:58:32
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CO_9268641302815242949907625
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
2024-08-16T14:46:10
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PO_2189240859700504570004707
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MD_1531921544206064124007380
null
[ "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_7_10", "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_9_5", "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_11_12", "Sb_iter0_T930_2_mp-133_elastic_B222_dist03_5_9" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_9276377171997029454397987
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
Sb8
Sb
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CO_9276377171997029454397987
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_9276377171997029454397987
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_9276377171997029454397987
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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2024-08-16T15:20:48
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CO_9293279856095894793614600
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_9293279856095894793614600
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_9293279856095894793614600
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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[ "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_7_10", "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_9_5", "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_11_3", "Sb_iter0_T930_1_mp-1179605_elastic_B222_dist03_5_4" ]
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CO_9293279856095894793614600
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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2024-08-16T15:37:51
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2023-12-01T22:58:31
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CO_9313225726600075530576670
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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2023-12-01T22:58:32
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CO_9354998302346044856934145
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
2024-08-16T15:20:29
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2023-12-01T22:58:32
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CO_9412623175690978522496959
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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MD_1213582242930949697188121
2024-08-16T14:26:54
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PO_4453300929451544493627777
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MD_8723377259784243212242054
null
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2023-12-01T22:58:32
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CO_9450897664829959628046875
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
2024-08-16T14:28:45
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PO_5177434438370264720297653
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MD_3072275598411872336810647
null
[ "Sb_iter2_11_mp-10630_elastic_B222_dist03_10_930_4" ]
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2023-12-01T22:58:32
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CO_9472529762245312753616479
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
2024-08-16T14:46:04
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MD_1189900988700438461574101
null
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2023-12-01T22:58:32
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CO_9489413560394223229678603
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
2024-08-16T15:22:47
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_9498701660572173937630139
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
2024-08-16T15:00:28
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PO_2648246289823267626994990
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MD_1069713809891562784388190
null
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2023-12-01T22:58:32
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CO_9501942693101669117083263
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
2024-08-16T15:38:59
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PO_1074344779207095563489049
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_9504395683474725745112848
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
2024-08-16T15:41:36
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PO_9547023143669612644033668
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MD_1189900988700438461574101
null
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2023-12-01T22:58:31
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CO_9515880178741894947289218
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
2024-08-16T14:57:31
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PO_1120320005293172593248423
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MD_6196355602623336221701784
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2023-12-01T22:58:32
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CO_9521779541440123994745938
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
2024-08-16T15:21:27
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PO_1006392304602542609872923
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MD_6774213934135675701540773
null
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2023-12-01T22:58:32
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CO_9531122817981205071676164
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
2024-08-16T15:38:12
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PO_8555944455626303226970891
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MD_1329574950964754993516039
null
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2023-12-01T22:58:31
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CO_9561966784504671046367164
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
2024-08-16T15:02:35
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PO_5914351219614075841024941
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MD_2164565307674838913500201
null
[ "Sb_iter0_T232_6_mp-7761_elastic_B222_dist03_8_8" ]
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2023-12-01T22:58:32
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CO_9565530474213534062135444
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
2024-08-16T14:46:29
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PO_4566360439394844779735013
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MD_1271418612909851697008258
null
[ "Sb_iter0_T930_11_mp-10630_elastic_B222_dist03_6_13" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_9611264235976771639307446
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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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
Sb
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MD_1213582242930949697188121
2024-08-16T14:27:06
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PO_4308104855069476283416327
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MD_1531921544206064124007380
null
[ "Sb_iter0_T232_2_mp-133_15" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:32
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CO_9620735954311928412699780
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}
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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
2024-08-16T14:35:16
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PO_9818130738900107484327791
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MD_1175204308310345149590984
null
[ "Sb_iter0_T930_0_mp-104_elastic_B222_dist03_7_9" ]
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2023-12-01T22:58:32
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CO_9621897257731524806537090
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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VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:39:36
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PO_3427524171559242815759451
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MD_1531921544206064124007380
null
[ "Sb_iter0_T930_2_mp-133_vacancies_Vac_0_4" ]
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2023-12-01T22:58:32
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CO_9632597192189030887587019
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
2024-08-16T15:06:01
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PO_9585550941609422995329513
{"materials-project-id": "mp-1179605", "temperature": 930, "hash": "10697138098915627843881903649647606609210529557860022746790534547878579860622982328899069195136728065135352912118809378780469320443629179075558145997738683", "id": "MD_1069713809891562784388190"}
MD_1069713809891562784388190
null
[ "Sb_iter2_1_mp-1179605_elastic_B222_dist03_10_930_9" ]
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2023-12-01T22:58:32
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CO_9637702889813852438721274
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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2023-12-01T22:58:31
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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
2024-08-16T14:35:31
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2023-12-01T22:58:32
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CO_9647173638348781631785021
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
2024-08-16T14:30:05
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PO_9288917102287800837121118
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_9695357036876776241722991
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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2024-08-16T15:14:41
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2023-12-01T22:58:32
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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
2024-08-16T14:32:46
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MD_1271418612909851697008258
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2023-12-01T22:58:32
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CO_9719521915104645492711985
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
2024-08-16T15:40:20
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MD_1069713809891562784388190
null
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2023-12-01T22:58:32
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CO_9721500515819929927108197
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
2024-08-16T15:33:31
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PO_1153742745385260726275229
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MD_1226566192249423389047690
null
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2023-12-01T22:58:32
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CO_9736291113689500514262502
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
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MD_1213582242930949697188121
2024-08-16T15:13:21
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PO_9576104362422653571331918
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MD_1329574950964754993516039
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2023-12-01T22:58:32
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CO_9759192029797204290177021
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
Sb17
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MD_1213582242930949697188121
2024-08-16T14:57:22
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PO_1349220309830888000803886
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MD_2164565307674838913500201
null
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2023-12-01T22:58:32
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CO_9779429349415883301703736
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
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MD_1213582242930949697188121
2024-08-16T15:29:58
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MD_1226566192249423389047690
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2023-12-01T22:58:32
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CO_9789100826762108806507599
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
2024-08-16T15:14:06
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2023-12-01T22:58:32
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CO_9790750470524916031591702
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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2024-08-16T14:24:42
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CO_9798384242387910179078153
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
2024-08-16T15:41:32
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2023-12-01T22:58:32
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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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2024-08-16T14:26:57
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2023-12-01T22:58:32
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CO_9804257312807083188860596
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
2024-08-16T14:30:44
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2023-12-01T22:58:32
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CO_9808307235871610407588657
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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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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CO_9892374289611196583948245
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
2024-08-16T14:39:01
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PO_2351001219044106946364357
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MD_2164565307674838913500201
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2023-12-01T22:58:32
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CO_9892374289611196583948245
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
2024-08-16T14:46:08
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MD_6196355602623336221701784
null
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2023-12-01T22:58:32
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CO_9908625686966144348868068
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
2024-08-16T15:42:42
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MD_1531921544206064124007380
null
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2023-12-01T22:58:31
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CO_9941632468489241475174977
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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{"input": {"ALGO": "fast", "EDIFF": "1E-8", "ENCUT": "400", "IBRION": "0", "ICHARG": "0", "ISIF": "2", "ISMEAR": "1", "ISTART": "0", "ISYM": "0", "KBLOCK": "10", "KGAMMA": "F", "KPAR": "16", "KSPACING": "0.24", "LCHARG": "T", "LREAL": "F", "LWAVE": "F", "MAXMIX": "50", "NBLOCK": "1", "NELM": "200", "NELMIN": "4", "NPAR": "8", "POTIM": "2", "PREC": "A", "PSTRESS": "0", "SIGMA": "0.15", "SMASS": "-1", "file-type": "INCAR"}, "hash": "12135822429309496971881212100548754870478961791137930949625877367285087883313386750731592539663054471050405358418449513543996992751906584969573924479043013", "id": "MD_1213582242930949697188121"}
MD_1213582242930949697188121
2024-08-16T15:35:46
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PO_8614604811783663588373316
{"materials-project-id": "mp-7761", "temperature": 232, "hash": "6774213934135675701540773796729302629317554541035381100152130003466711489090000370856816777870328604323851771860481613575171186235492398971819959733875247", "id": "MD_6774213934135675701540773"}
MD_6774213934135675701540773
null
[ "Sb_iter1_6_mp-7761_elastic_B222_dist03_9_232_7" ]
[ "DS_z90lfjg88fzo_0" ]
2023-12-01T22:58:31
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CO_9944455712683657047837631
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