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[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:45:10
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:34:50
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2023-12-01T22:52:29
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CO_1071040561425426935861300
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:44:39
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_6804590236965634482882577
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
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MD_1213582242930949697188121
2024-08-16T15:21:44
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PO_5221235646040271663001073
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_4_6" ]
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2023-12-01T22:52:29
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CO_1062391831669405082411291
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:49:31
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PO_7769691729736905430506936
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_17" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1230489701676613860297845
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
[ [ 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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
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2024-08-16T14:29:00
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2023-12-01T22:52:29
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CO_3637423705077484830496419
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:15:24
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_1478617883835305595771558
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:28:54
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MD_9300119296539735821808460
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2023-12-01T22:52:29
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CO_4934225881203004003984904
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_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
2024-08-16T15:00:40
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PO_1190726175627340048467975
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_7_1" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_9291018142831635326515239
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
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MD_1213582242930949697188121
2024-08-16T15:07:20
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MD_8342077683094605614607324
null
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2023-12-01T22:52:29
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CO_4750385406091531456064837
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:08:01
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PO_4921799614274774045245568
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MD_8167787933279587874418320
null
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2023-12-01T22:52:29
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CO_2188150599697979847230360
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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MD_1213582242930949697188121
2024-08-16T15:24:51
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PO_5281601962744626277829213
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter1_1_mp-1183144_elastic_B222_dist03_0_2" ]
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2023-12-01T22:52:29
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CO_4275585963127753426122012
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al7
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VASP
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MD_1213582242930949697188121
2024-08-16T15:28:42
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PO_4606924201979157298656223
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_vacancies_Vac_0_8" ]
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2023-12-01T22:52:29
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CO_7589183279302257736007491
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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MD_1213582242930949697188121
2024-08-16T14:29:57
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PO_1190708405584804662481633
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_16" ]
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2023-12-01T22:52:29
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CO_9896563264922100491772011
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
Al
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1
VASP
DFT-PBE
null
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null
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true
null
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null
2.951897
11.671198
{"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
2024-08-16T15:31:31
1598732283129245161762599918415921542198718431526251163479295026609518410853561566217559428178261942397202463932305017354829976730279141952293845237749558
PO_1598732283129245161762599
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_10" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
10725101141487549987302036464622297493583923676973375747845264585044503952673264321090288952783265708425329844358513380348066432029152736924799983775706716
CO_1072510114148754998730203
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
1
2,572
2,572
88,139
0
2,572
0
2,572
0
2,572
-97.865127
3,139.699139
0
2023-12-01T17:52:38
[ [ 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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
Al
A
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[ "Al" ]
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[ true, true, true ]
[ 1, 1, 1 ]
3
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1
VASP
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2024-08-16T15:36:35
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2023-12-01T22:52:29
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CO_2948543099175139910670871
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:28:58
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PO_6296376934693726547900148
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_9723836346389114063221049
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:52:29
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CO_9490672637985825679597419
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:16:48
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PO_9492607932966209836833977
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_4_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1034085077524151572213650
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al33
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MD_1213582242930949697188121
2024-08-16T14:41:21
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_13" ]
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2023-12-01T22:52:29
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CO_5209169892461903576937812
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:21:54
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MD_8342077683094605614607324
null
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2023-12-01T22:52:29
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CO_4750093198536335082893931
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T14:39:17
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CO_2931811971391487473664700
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:23:03
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_2329245696696403652475659
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:06:29
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2023-12-01T22:52:29
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CO_4430927468723916883755422
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:40:48
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_5_3" ]
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2023-12-01T22:52:29
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CO_1331413845375954360919706
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:31:07
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PO_2773451956348275851850481
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_7" ]
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2023-12-01T22:52:29
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CO_8901528529234266373888203
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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MD_1213582242930949697188121
2024-08-16T15:37:30
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:18:16
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_3170703348616903762212681
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T15:40:17
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2023-12-01T22:52:29
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CO_5719669874623246154228425
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T15:28:53
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2023-12-01T22:52:29
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CO_5844417396481076682591462
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:23:37
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2023-12-01T22:52:29
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:41:09
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PO_3997483692422874034912122
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_1_3" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_9195985409301787490365994
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
A
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[ "Al" ]
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1
VASP
DFT-PBE
null
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null
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MD_1213582242930949697188121
2024-08-16T14:29:48
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PO_2190655467472287811917393
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter1_0_mp-134_elastic_B222_dist03_0_5" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_5207996764921384218789213
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
1
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2,572
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2023-12-01T17:52:38
[ [ 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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al7
Al
A
[ 13, 13, 13, 13, 13, 13, 13 ]
[ "Al" ]
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1
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1
VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:34:02
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PO_1231566064420007553576294
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_vacancies_10" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1955228048067860022168807
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2,572
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3,139.699139
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2023-12-01T17:52:38
[ [ 1, 1, 1 ] ]
[ 3 ]
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
Al
A
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[ "Al" ]
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MD_1213582242930949697188121
2024-08-16T14:55:02
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PO_3494159973957468507636901
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_2_1" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_3972988041617147720646472
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
A
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MD_1213582242930949697188121
2024-08-16T15:00:21
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_2" ]
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2023-12-01T22:52:29
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CO_3225334951302086671450307
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:27:47
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PO_5378072911881673813301283
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_17" ]
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2023-12-01T22:52:29
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CO_5369143360046924633185445
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:37:15
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MD_8167787933279587874418320
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2023-12-01T22:52:29
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CO_2359529256367941001711824
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:14:37
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null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_9", "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_13" ]
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2023-12-01T22:52:29
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CO_3279483184087169504734278
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:35:50
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2023-12-01T22:52:29
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CO_5254782869447179146926581
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T15:33:04
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:50:57
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2023-12-01T22:52:29
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CO_1219803146695214255575355
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:17:09
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MD_8167787933279587874418320
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[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_6" ]
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2023-12-01T22:52:29
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CO_9661122607105507230726906
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:15:21
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2023-12-01T22:52:29
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CO_1778522424378388464260163
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2023-12-01T22:52:29
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CO_8242319831457866523351756
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
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CO_1261697678671396005780612
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
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2023-12-01T22:52:29
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CO_5496263711227083180405172
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T15:24:41
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null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_interOh_5" ]
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2023-12-01T22:52:29
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CO_1184338069790633367201902
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:53:57
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MD_8167787933279587874418320
null
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2023-12-01T22:52:29
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CO_7594728907610599874788631
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T15:29:36
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MD_9300119296539735821808460
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2023-12-01T22:52:29
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CO_1144826725857345981884268
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
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MD_1213582242930949697188121
2024-08-16T15:00:24
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PO_9048305271796452129557527
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_2_1" ]
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2023-12-01T22:52:29
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CO_1106720924253408612353063
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
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MD_1213582242930949697188121
2024-08-16T14:27:50
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PO_1979266950344754291386840
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_5" ]
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2023-12-01T22:52:29
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CO_9392278760679128788570576
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
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CO_4309079790002301374665540
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:36:10
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PO_8606200188218844082408835
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_8862931396024557627609384
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:12:29
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_interOh_9" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1062657487598626201050301
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
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MD_1213582242930949697188121
2024-08-16T14:22:05
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_3388535005536058594291385
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
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MD_1213582242930949697188121
2024-08-16T14:38:29
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PO_1093671069107544803208130
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_13" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_5233562847422894472251341
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:11:40
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2023-12-01T22:52:29
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CO_1216156471759945954235128
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
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MD_1213582242930949697188121
2024-08-16T15:06:12
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_5341688249291817460516104
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
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MD_8342077683094605614607324
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CO_5588087626280100350064626
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
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MD_1213582242930949697188121
2024-08-16T14:15:50
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_2147759733471976184229866
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:30:35
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2023-12-01T22:52:29
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CO_7103947290235962700811019
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:12:30
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2023-12-01T22:52:29
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CO_1116510354456842549397025
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:23:30
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[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_0", "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_13" ]
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2023-12-01T22:52:29
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CO_9508105443846096546014679
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:57:48
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2023-12-01T22:52:29
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CO_8920803869060593252995786
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T22:52:29
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CO_1160582876535775738781905
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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[ "Al" ]
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MD_1213582242930949697188121
2024-08-16T15:11:43
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PO_5865258205744722439058819
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter1_0_mp-134_elastic_B222_dist03_5_5" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_2786737176057087544360081
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al31
Al
A
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MD_1213582242930949697188121
2024-08-16T14:22:46
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PO_4176003789438889736380909
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_vacancies_Vac_0_13" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_9534913909404513376653922
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
[ [ 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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
A
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MD_1213582242930949697188121
2024-08-16T14:45:03
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T240_2_mp-998860_elastic_7" ]
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2023-12-01T22:52:29
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CO_5710622663198868508584194
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8342077683094605614607324
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2023-12-01T22:52:29
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CO_6747640208508653818485974
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al33
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2024-08-16T14:21:57
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null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_interTd_11" ]
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2023-12-01T22:52:29
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CO_2093306506667181752123038
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:17:36
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_19" ]
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2023-12-01T22:52:29
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CO_1044020765109469894577016
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:25:12
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null
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2023-12-01T22:52:29
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CO_2749789042527679041184521
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:58:43
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_5967358251357778032255024
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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2024-08-16T14:34:02
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null
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2023-12-01T22:52:29
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CO_1092371701321544398158818
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:29:09
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2023-12-01T22:52:29
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CO_1263287959840240901421427
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T15:33:29
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PO_1289997750047461805696404
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null
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2023-12-01T22:52:29
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CO_1897727420854638293627266
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al7
Al
A
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MD_1213582242930949697188121
2024-08-16T15:21:08
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PO_2516068575046596385733256
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_vacancies_17" ]
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2023-12-01T22:52:29
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CO_3467675943683274424086465
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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A
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MD_1213582242930949697188121
2024-08-16T15:11:01
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PO_1285002826889501552573847
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_9" ]
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2023-12-01T22:52:29
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CO_3466371703886567215689104
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:38
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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/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al16
Al
A
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MD_1213582242930949697188121
2024-08-16T14:43:49
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null
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:53:50
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2023-12-01T22:52:29
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CO_1701344151253571448532837
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:33:35
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_1060377067387622422962402
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2023-12-01T17:52:38
[ [ 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}
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al64
Al
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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
2024-08-16T14:23:09
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PO_1190970328930377586716539
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_15" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_4699352269715776885109359
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
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2023-12-01T17:52:38
[ [ 1, 1, 1 ] ]
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
Al
A
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2024-08-16T14:35:01
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:34:29
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MD_9300119296539735821808460
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2023-12-01T22:52:29
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CO_9093192122795972574805581
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:23:22
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_4998384105497906036078540
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:36:46
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PO_1080051052465479063951796
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_19" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1297151563851099483994165
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al31
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MD_1213582242930949697188121
2024-08-16T15:16:33
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PO_5272313123639657676065371
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_vacancies_12" ]
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2023-12-01T22:52:29
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CO_1264646967703220785275978
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al15
Al
A
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MD_1213582242930949697188121
2024-08-16T14:26:33
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2023-12-01T22:52:29
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CO_3116242328411566488075797
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:05:09
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_5601374810082880725651379
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
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MD_1213582242930949697188121
2024-08-16T14:59:49
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2023-12-01T22:52:29
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CO_8372549146913944754764218
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:13:26
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2023-12-01T22:52:29
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CO_9858928057221325835084473
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Al__Andolina-Saidi__DS_8y775we7um7w_0
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2024-08-16T14:51:49
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CO_4768039202085811228318028
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:12:31
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2023-12-01T22:52:29
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CO_3612796753147292651288007
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T14:34:56
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2023-12-01T22:52:29
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CO_1145564363619262476524745
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
VASP
DFT-PBE
null
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null
[ [ 25.772794723510742, 0.4605199992656708, -0.22870199382305145 ], [ 0.4605199992656708, 22.72072410583496, -1.0795910358428955 ], [ -0.22870199382305145, -1.0795910358428955, 21.031768798828125 ] ]
true
null
null
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null
1.062458
4.739909
{"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
2024-08-16T15:19:27
3352616103787143974251152813578720275489464550539832993308268624369933584144916485449459901553559286161804091905838046631267953354316673570571964255350517
PO_3352616103787143974251152
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_interOh_16" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
2517514016592985332492139690949498293125763633764047092434695433197385749764978297485924067181200035209224414569015078888835625867886514552627299276350594
CO_2517514016592985332492139
23-Single-Element-DNPs_RSCDD_2023-Al
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Al from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Al" ]
1
2,572
2,572
88,139
0
2,572
0
2,572
0
2,572
-97.865127
3,139.699139
0
2023-12-01T17:52:38
[ [ 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/ef6f5966
7689231455410618897560052124104137364056795375282966294498570137054427401588023463237470940226529647977948884543399570947095496860696162620668064202700572
DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0