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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
[ "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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2024-08-16T14:52:39
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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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2024-08-16T14:51:40
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2023-12-01T22:52:29
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CO_1110715483122852620942036
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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2024-08-16T14:23:39
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null
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2023-12-01T22:52:29
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CO_3987587887252966761461807
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
2024-08-16T15:18:08
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2023-12-01T22:52:29
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CO_5320170933593729943472845
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
[ "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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CO_4679685360297441297253392
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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CO_1164071850204693528950006
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}
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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{"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
2024-08-16T15:18:25
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PO_3104452445485254345858724
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter1_0_mp-134_elastic_B222_dist03_5_6" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_5532992550080757737492162
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
[ 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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MD_1213582242930949697188121
2024-08-16T14:27:23
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PO_9094658952159847090279351
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_9_2" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_7590373635034228007074000
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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null
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MD_1213582242930949697188121
2024-08-16T14:13:41
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PO_1007247535766547504651200
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_2" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_2868945476380493792560875
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
A
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MD_1213582242930949697188121
2024-08-16T14:24:23
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_4971874794407699041238789
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
2024-08-16T14:51:00
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_14" ]
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2023-12-01T22:52:29
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CO_1298665148119966750546397
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}
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al7
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MD_1213582242930949697188121
2024-08-16T15:39:34
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2023-12-01T22:52:29
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CO_5436890484380629296853506
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
2024-08-16T15:08:40
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2023-12-01T22:52:29
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CO_1242096358749643109926272
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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MD_1213582242930949697188121
2024-08-16T14:37:54
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PO_1200772844323815200684922
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_3862423640721980015031255
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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CO_5809212949974229768648097
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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2024-08-16T15:10:16
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2023-12-01T22:52:29
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CO_1307816303320535562358712
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
2024-08-16T15:29:08
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_16" ]
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2023-12-01T22:52:29
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CO_6839820535560926186131299
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
2024-08-16T14:33:29
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PO_1242848135841607897514547
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_18" ]
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2023-12-01T22:52:29
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CO_1993725151416463423630271
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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2024-08-16T14:12:14
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2023-12-01T22:52:29
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CO_1318880048520413686635958
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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2024-08-16T15:05:49
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2023-12-01T22:52:29
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CO_4386344113185456362193264
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
2024-08-16T15:18:07
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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
2024-08-16T14:17:08
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2023-12-01T22:52:29
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CO_5137961727476084740377571
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
2024-08-16T15:17:35
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PO_2753469873899464412283027
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_5" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1266080484448930133286174
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
[ 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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MD_1213582242930949697188121
2024-08-16T14:29:42
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PO_6177354265988614349526463
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_6" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_6416924121127473627931770
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
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
2024-08-16T14:52:08
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PO_1041401194412281817820277
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_1" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_5465660656918066014686669
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
Al64
Al
A
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MD_1213582242930949697188121
2024-08-16T14:53:45
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2023-12-01T22:52:29
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CO_2435386793718875252675832
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
2024-08-16T15:32:31
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PO_1385067588540215259994050
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T240_2_mp-998860_elastic_13" ]
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2023-12-01T22:52:29
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CO_2036538086482838767316205
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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2024-08-16T14:13:09
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2023-12-01T22:52:29
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CO_1048522349350676941284487
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
2024-08-16T14:18:12
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2023-12-01T22:52:29
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CO_5715646744378692935532040
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
2024-08-16T14:54:40
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_vacancies_Vac_0_2" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1028109335390358736906819
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
2024-08-16T14:30:10
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PO_9787422144887718741383696
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_6" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_6948550596556332536252189
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
2024-08-16T14:12:37
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MD_9300119296539735821808460
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[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_7" ]
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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
2024-08-16T14:15:53
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_1369753095865777879094286
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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2024-08-16T14:13:22
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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
2024-08-16T14:50:10
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_4049062947055388339534392
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
2024-08-16T14:34:17
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2023-12-01T22:52:29
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CO_1319190421983520181175560
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
2024-08-16T14:44:03
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_1041242103986459830794926
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
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MD_1213582242930949697188121
2024-08-16T14:52:12
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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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2023-12-01T22:52:29
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CO_9138468604375857546299740
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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2024-08-16T15:39:35
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MD_9300119296539735821808460
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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
2024-08-16T15:15:32
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MD_9300119296539735821808460
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2023-12-01T22:52:29
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CO_1054874462788809742756941
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
2024-08-16T14:31:00
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null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_2", "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_9" ]
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2023-12-01T22:52:29
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CO_8680324202896133355504789
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
2024-08-16T15:14:15
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_8" ]
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2023-12-01T22:52:29
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CO_4922911479219220754744152
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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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
2024-08-16T15:01:37
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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
Al16
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2024-08-16T14:12:38
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MD_1092689733835166895275909
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CO_1234273546858823880131851
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
2024-08-16T14:41:55
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PO_1089156525085803222969845
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T960_8_mp-1239196_elastic_16" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_2187896611369538026444503
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}
10.60732/ef6f5966
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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
2024-08-16T14:48:09
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_0", "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_9" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1302816662135408632167821
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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{"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
2024-08-16T14:48:13
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PO_3913367046669051308915703
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_15" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_4430197646118572728978261
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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[ 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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MD_1213582242930949697188121
2024-08-16T14:19:00
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PO_1211451818642474744773920
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_1030201648282468598202526
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
2024-08-16T15:37:11
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PO_2374901113186285671450644
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_interOh_0" ]
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2023-12-01T22:52:29
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CO_3474236694188578238938079
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
Al
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MD_1213582242930949697188121
2024-08-16T15:23:51
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2023-12-01T22:52:29
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CO_8898240534830535798725307
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
2024-08-16T14:57:15
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PO_1123302557958176832837880
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_2", "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_13" ]
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2023-12-01T22:52:29
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CO_7953076774150629544412927
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
2024-08-16T15:25:08
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PO_5133594175700913258992388
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_10_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_3240165603210288233028493
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
[ 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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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:14:14
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_11_5" ]
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2023-12-01T22:52:29
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CO_1242840258472175415020411
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
2024-08-16T15:40:39
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PO_1038829258046685515856264
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_elastic_1" ]
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2023-12-01T22:52:29
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CO_8991967046406425656716915
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
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MD_1213582242930949697188121
2024-08-16T14:54:14
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_12" ]
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2023-12-01T22:52:29
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CO_1104061834106857650188855
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
Al
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MD_1213582242930949697188121
2024-08-16T14:18:14
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_3280603152486682528663374
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
2024-08-16T14:23:48
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PO_5149494348018673207378979
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MD_9300119296539735821808460
null
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2023-12-01T22:52:29
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CO_3814755539081164652931724
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
2024-08-16T14:39:21
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2023-12-01T22:52:29
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CO_9225452769556136943748105
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
2024-08-16T15:09:51
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_8911085584109794027978797
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
2024-08-16T14:38:30
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null
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2023-12-01T22:52:29
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CO_6225774085763361204087765
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
2024-08-16T14:36:04
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T240_0_mp-134_interstitials_FCC2_5" ]
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2023-12-01T22:52:29
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CO_1059911353495728207531227
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
2024-08-16T14:45:35
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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
2024-08-16T14:19:33
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MD_1092689733835166895275909
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2023-12-01T22:52:29
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CO_1132862368079448565448989
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
2024-08-16T14:58:58
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[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_crowdion_10" ]
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2023-12-01T22:52:29
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CO_1064220889438776701685828
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
2024-08-16T15:39:12
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MD_8342077683094605614607324
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2023-12-01T22:52:29
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CO_3321975556586099283259155
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
Al64
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MD_1213582242930949697188121
2024-08-16T15:33:28
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PO_5902906196083572094735856
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_2_6" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_9719530355281140617535838
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}
10.60732/ef6f5966
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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
2024-08-16T15:25:31
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2023-12-01T22:52:29
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CO_2630943256821929958370385
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
2024-08-16T15:39:17
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2023-12-01T22:52:29
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CO_6908353395486103193667186
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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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
2024-08-16T14:19:22
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PO_9434356347313400140036906
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_1" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_6859488427802301491927910
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}
10.60732/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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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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2024-08-16T14:17:43
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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_9300119296539735821808460
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2023-12-01T22:52:29
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CO_6528440916212396873131029
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
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MD_1213582242930949697188121
2024-08-16T15:31:17
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PO_6188835226509437310372742
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter0_T960_2_mp-998860_elastic_1" ]
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2023-12-01T22:52:29
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CO_1315152307688914629901915
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}
10.60732/ef6f5966
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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
2024-08-16T15:07:17
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PO_2802298089685494160830525
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_17" ]
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2023-12-01T22:52:29
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CO_7728070023062170686484125
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
2024-08-16T15:18:19
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PO_3807974497885251291406454
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T960_1_mp-1183144_elastic_7" ]
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2023-12-01T22:52:29
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CO_8111227535563919257648646
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
Al64
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MD_1213582242930949697188121
2024-08-16T14:54:30
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PO_1034943786961860884058903
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter1_8_mp-1239196_elastic_B222_dist03_3_6" ]
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2023-12-01T22:52:29
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CO_6136867103564995379632943
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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MD_1213582242930949697188121
2024-08-16T14:19:33
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MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_interstitials_FCC2_db111_10" ]
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2023-12-01T22:52:29
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CO_6070788655848883677197347
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
2024-08-16T14:39:26
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PO_1306485799053249194892858
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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_3057737262580942099172980
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
Al
A
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MD_1213582242930949697188121
2024-08-16T15:11:06
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MD_1092689733835166895275909
null
[ "Al_iter_all_Al_iter1_2_mp-998860_elastic_B222_dist03_0_6" ]
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2023-12-01T22:52:29
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CO_1315552519946041469143362
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
2024-08-16T15:30:52
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MD_8342077683094605614607324
null
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2023-12-01T22:52:29
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CO_1256723251112141627018476
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
2024-08-16T14:42:30
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PO_9452416254240472042862332
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_6" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_7721973813374612965403661
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
[ 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
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MD_1213582242930949697188121
2024-08-16T14:27:41
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2023-12-01T22:52:29
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CO_6553207892936130604815552
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
2024-08-16T14:32:19
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2023-12-01T22:52:29
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CO_5072333806194639886691909
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
2024-08-16T14:45:29
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2023-12-01T22:52:29
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CO_7304139218323843686902129
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
Al64
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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
2024-08-16T15:29:04
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PO_7905392035005084843202580
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_7" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1308727357448500708025068
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}
10.60732/ef6f5966
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DS_8y775we7um7w_0
23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Al32
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2024-08-16T15:23:06
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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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{'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
2024-08-16T14:20:45
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2023-12-01T22:52:29
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CO_8459789118558789168293966
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
Al
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MD_1213582242930949697188121
2024-08-16T15:24:13
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MD_1092689733835166895275909
null
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2023-12-01T22:52:29
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CO_1030325240221391495468292
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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2024-08-16T15:41:42
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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
2024-08-16T15:22:58
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MD_8342077683094605614607324
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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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{'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
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MD_1213582242930949697188121
2024-08-16T14:13:17
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PO_6962162854230065651132776
{"materials-project-id": "mp-1239196", "hash": "8342077683094605614607324857260170669140498379261154861648293746153348359965509525658547092727097566869581532283708695391511341702084057581224555682625117", "id": "MD_8342077683094605614607324"}
MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_7" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1264038412056320741697984
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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[ "Al" ]
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MD_1213582242930949697188121
2024-08-16T14:48:14
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PO_4229611745600842907802110
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MD_8167787933279587874418320
null
[ "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_16", "Al_iter_all_Al_iter0_T240_1_mp-1183144_elastic_19" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_1190422213558821652877069
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
2024-08-16T15:22:20
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PO_1108426485472426050196371
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MD_8342077683094605614607324
null
[ "Al_iter_all_Al_iter0_T240_8_mp-1239196_elastic_0" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_9246478431795179023924589
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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DFT-PBE
null
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null
[ [ 118.52128601074219, 0.08468600362539291, 0.3559409976005554 ], [ 0.08468600362539291, 118.61825561523438, 0.3090139925479889 ], [ 0.3559409976005554, 0.3090139925479889, 118.78697204589844 ] ]
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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
2024-08-16T15:42:18
5910337447914396532854849860100018337650983548582970112035189176983489505301027518702680664122052158840036914427696419102046088579435256750071119429786082
PO_5910337447914396532854849
{"materials-project-id": "mp-134", "hash": "930011929653973582180846073299680827437022025687644079123128187039650194767557092970609420019523229875568620757991932789349995522096392043901851193061019", "id": "MD_9300119296539735821808460"}
MD_9300119296539735821808460
null
[ "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_3", "Al_iter_all_Al_iter0_T960_0_mp-134_elastic_15" ]
[ "DS_8y775we7um7w_0" ]
2023-12-01T22:52:29
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CO_7564993150092113746391302
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
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2,572
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2,572
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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