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

Dataset card Data Studio Files Community
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Pd32
Pd
A
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[ "Pd" ]
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null
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MD_1213582242930949697188121
2024-08-16T14:35:20
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MD_7739915350941659843248639
null
[ "Pd_iter1_Pd_3_txDUqr43LI0W6aW6UqXUmOzM23Gi_elastic_B222_dist03_9_2100_8" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9111147722478424349263857
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
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[ 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}
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
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MD_1213582242930949697188121
2024-08-16T15:33:19
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T525_4_diamond_elastic_B222_dist03_1_4" ]
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2023-12-01T22:57:35
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CO_9112493238998183351850746
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
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MD_1213582242930949697188121
2024-08-16T14:49:15
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PO_2924065006812495445219567
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MD_1230274224906835886776657
null
[ "Pd_iter1_Pd_0_mp-2_elastic_B222_dist03_4_2100_7" ]
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2023-12-01T22:57:35
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CO_9116893992036385513914116
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
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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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd33
Pd
A
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MD_1213582242930949697188121
2024-08-16T14:33:37
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2023-12-01T22:57:35
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CO_9153761667437514205578905
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
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MD_1213582242930949697188121
2024-08-16T14:33:22
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MD_1086845055867124744315202
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2023-12-01T22:57:35
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CO_9158412039872905356602169
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
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MD_1213582242930949697188121
2024-08-16T14:52:32
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PO_7115108931104291687236573
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MD_3224333442521978667250005
null
[ "Pd_iter1_Pd_1_mp-1186427_elastic_B222_dist03_0_2100_3" ]
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2023-12-01T22:57:35
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CO_9160386386132471646072152
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:38:11
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MD_1086845055867124744315202
null
[ "Pd_iter1_Pd_3_txDUqr43LI0W6aW6UqXUmOzM23Gi_elastic_B222_dist03_10_6" ]
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2023-12-01T22:57:35
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CO_9162204418097085166025840
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
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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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:29:41
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PO_5351012246503248025566680
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_B222_dist03_3_2" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9189841422776264795638732
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
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140,196
0
3,478
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3,478
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3,478
-158.91135
12,101.314813
0
2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:01:10
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_B222_dist03_10_0" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9193690066795539113728088
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:06
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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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd33
Pd
A
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MD_1213582242930949697188121
2024-08-16T15:10:07
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PO_2621147645536778730480175
{"materials-project-id": "mp-2", "temperature": 2100, "hash": "12302742249068358867766577539024291395767582302523952475815447343846140000053222063854725359262256273907218665191021942570888320256245613213039806046557174", "id": "MD_1230274224906835886776657"}
MD_1230274224906835886776657
null
[ "Pd_iter2_Pd_0_mp-2_interstitials_FCC2_db111_2100_3" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9199209034161083683176323
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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MD_1213582242930949697188121
2024-08-16T15:34:10
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MD_1086845055867124744315202
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2023-12-01T22:57:35
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CO_9211499570493069664708714
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T15:31:38
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PO_6385518312968646470588326
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MD_8649137601690553188904937
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2023-12-01T22:57:35
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CO_9213025786516318550002950
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
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MD_1213582242930949697188121
2024-08-16T15:32:05
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CO_9246168012735110477669796
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T14:29:34
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MD_8649137601690553188904937
null
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2023-12-01T22:57:35
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CO_9253912343120331822227036
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:06
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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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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1
VASP
DFT-PBE
null
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true
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MD_1213582242930949697188121
2024-08-16T15:18:00
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PO_1106871519942291126779299
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_4_diamond_elastic_B222_dist03_11_18" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9269595925655591492647986
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
3,478
140,196
0
3,478
0
3,478
0
3,478
-158.91135
12,101.314813
0
2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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1
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1
VASP
DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T14:59:39
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PO_4819742739708399996276679
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_4_diamond_elastic_B222_dist03_1_13" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9282634829257124834866934
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
3,478
140,196
0
3,478
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3,478
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2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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MD_1213582242930949697188121
2024-08-16T15:42:32
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CO_9292502361465992182845778
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T15:29:21
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MD_1086845055867124744315202
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2023-12-01T22:57:35
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CO_9310552546763349983370168
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T14:45:28
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CO_9317447991446565711569590
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:32:10
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MD_1171791136443664841782881
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2023-12-01T22:57:35
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CO_9338243581202512206895168
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T14:35:27
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null
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2023-12-01T22:57:35
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CO_9348958520494743959975200
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
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MD_1213582242930949697188121
2024-08-16T15:42:38
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_B222_dist03_10_15" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9349437352720687103297923
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
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140,196
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3,478
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3,478
0
3,478
-158.91135
12,101.314813
0
2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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1
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:29:19
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PO_1312368790805902995151015
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_4_diamond_elastic_B222_dist03_9_14" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9357357757572269007633282
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
[ [ 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}
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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MD_1213582242930949697188121
2024-08-16T14:59:06
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PO_1008413378085009558925196
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MD_7739915350941659843248639
null
[ "Pd_iter1_Pd_4_diamond_elastic_B222_dist03_9_2100_7" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9376535446585116458662548
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
[ [ 1, 1, 1 ] ]
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2023
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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1
VASP
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CO_9398353923726492724850649
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:16:57
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T525_4_diamond_elastic_B222_dist03_0_19" ]
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2023-12-01T22:57:35
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CO_9423178796838202441451684
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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MD_1213582242930949697188121
2024-08-16T15:02:02
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_3_txDUqr43LI0W6aW6UqXUmOzM23Gi_elastic_B222_dist03_4_11" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9425742268668276599485296
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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MD_1213582242930949697188121
2024-08-16T14:55:22
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2023-12-01T22:57:35
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CO_9437730077535188765188920
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:29:36
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T525_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_vacancies_Vac_0_7" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9438078602045243275521624
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T15:03:58
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PO_2823589316864880948291063
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MD_1171791136443664841782881
null
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2023-12-01T22:57:35
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CO_9448710282125577053617396
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T14:37:50
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2023-12-01T22:57:35
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CO_9450619972702560339152579
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:54:36
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MD_1086845055867124744315202
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2023-12-01T22:57:35
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CO_9465569396190385757401944
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd7
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MD_1213582242930949697188121
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CO_9469594284805371525692053
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
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2024-08-16T14:34:27
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MD_1086845055867124744315202
null
[ "Pd_iter1_Pd_3_txDUqr43LI0W6aW6UqXUmOzM23Gi_elastic_B222_dist03_5_8" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9470532476006115709332066
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd31
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MD_1213582242930949697188121
2024-08-16T14:46:32
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PO_3077031901577638021300862
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MD_1171791136443664841782881
null
[ "Pd_iter1_Pd_0_mp-2_vacancies_Vac_0_7" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9491115973878776147403893
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
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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}
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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MD_1213582242930949697188121
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MD_1171791136443664841782881
null
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2023-12-01T22:57:35
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CO_9499389504158869006471951
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd8
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MD_1213582242930949697188121
2024-08-16T14:35:26
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MD_1086845055867124744315202
null
[ "Pd_iter1_Pd_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_dist03_7_1" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9528491201853961256995072
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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MD_1213582242930949697188121
2024-08-16T14:49:00
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T525_4_diamond_elastic_B222_dist03_4_12" ]
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2023-12-01T22:57:35
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CO_9533540358868665073910237
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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MD_1213582242930949697188121
2024-08-16T15:41:04
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T525_3_txDUqr43LI0W6aW6UqXUmOzM23Gi_elastic_B222_dist03_11_8" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9537989039410903180079356
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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MD_1213582242930949697188121
2024-08-16T14:50:17
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PO_9382983412903717338753842
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MD_1210149765697517309887518
null
[ "Pd_iter1_Pd_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_B222_dist03_11_525_5" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9538544964999831278930481
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
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140,196
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3,478
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0
3,478
-158.91135
12,101.314813
0
2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
[ 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46, 46 ]
[ "Pd" ]
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1
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DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T14:31:40
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PO_7150097964874851344040418
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_3_txDUqr43LI0W6aW6UqXUmOzM23Gi_elastic_B222_dist03_1_11" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9539751960872698838501037
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
[ [ 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}
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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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
2024-08-16T15:09:39
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PO_1271193287829763152293532
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T525_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_B222_dist03_3_13", "Pd_iter0_Pd_iter0_T525_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_B222_dist03_3_19" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9545771502343074444912118
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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VASP
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23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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CO_9565435544500634512623351
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
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MD_1213582242930949697188121
2024-08-16T15:19:01
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MD_1086845055867124744315202
null
[ "Pd_iter0_Pd_iter0_T2100_4_diamond_elastic_B222_dist03_10_1" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9586930773195942956247905
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
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2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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[ "Pd" ]
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2024-08-16T14:56:12
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2023-12-01T22:57:35
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CO_9605991517803853067942729
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:40:49
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2023-12-01T22:57:35
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CO_9631922173027132632327852
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T14:36:17
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MD_1171791136443664841782881
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2023-12-01T22:57:35
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CO_9687488746197713494929905
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:06
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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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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[ "Pd" ]
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1
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1
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DFT-PBE
null
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null
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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
2024-08-16T15:22:53
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PO_7279565089561722459594835
{"materials-project-id": "mp-1186427", "hash": "10315276432911537287063986735124010552461057924858147626121883703942830269025942674362460837483953132681649791485586703864913704608976745185922321695676346", "id": "MD_1031527643291153728706398"}
MD_1031527643291153728706398
null
[ "Pd_iter1_Pd_1_mp-1186427_elastic_B222_dist03_3_9" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9705406660944021697700570
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
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140,196
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3,478
0
3,478
0
3,478
-158.91135
12,101.314813
0
2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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VASP
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2024-08-16T14:33:48
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2023-12-01T22:57:35
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CO_9709725935421740379637230
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:29:52
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2023-12-01T22:57:35
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CO_9722710052723614190050569
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1171791136443664841782881
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[ "Pd_iter1_Pd_0_mp-2_elastic_B222_dist03_9_0" ]
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CO_9726068091431222550277884
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T15:37:48
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2023-12-01T22:57:35
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CO_9731276573136335499928797
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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CO_9735137392507842713554322
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T15:17:47
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CO_9757064582119455385796116
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
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CO_9779586095865578102033206
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
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MD_1086845055867124744315202
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CO_9792971781799249657275668
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
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1
VASP
DFT-PBE
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true
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MD_1213582242930949697188121
2024-08-16T14:51:33
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PO_1324178858557810319128809
{"temperature": 525, "hash": "12101497656975173098875184047855931446224718436092089661545130442223057798317910340368506192847432000730306899114793466510119978060564034489577350941692128", "id": "MD_1210149765697517309887518"}
MD_1210149765697517309887518
null
[ "Pd_iter1_Pd_4_diamond_elastic_B222_dist03_6_525_7" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9806313853509785423207891
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
3,478
140,196
0
3,478
0
3,478
0
3,478
-158.91135
12,101.314813
0
2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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[ "Pd" ]
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1
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1
VASP
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MD_1213582242930949697188121
2024-08-16T15:13:01
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CO_9841015947032647187467673
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:51:36
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MD_1086845055867124744315202
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2023-12-01T22:57:35
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CO_9881947924594475239071390
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T14:32:02
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MD_8623581532269720749474932
null
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2023-12-01T22:57:35
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CO_9903408013527194174895027
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd8
Pd
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VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:19:43
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PO_3001856345469724611371515
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MD_1210149765697517309887518
null
[ "Pd_iter2_Pd_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_dist03_5_525_0" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9908991602685403356534059
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:06
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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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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MD_1213582242930949697188121
2024-08-16T15:26:46
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MD_1086845055867124744315202
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2023-12-01T22:57:35
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CO_9910931966212736104147983
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:13:03
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PO_1056529207217746522351523
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MD_8649137601690553188904937
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2023-12-01T22:57:35
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CO_9946729909282743831338258
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T15:13:57
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PO_1863728340576897243014862
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MD_8623581532269720749474932
null
[ "Pd_iter2_Pd_0_mp-2_elastic_B222_dist03_5_525_2" ]
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2023-12-01T22:57:35
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CO_9952877703373055172711481
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:42:47
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PO_1469399417720932565640307
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MD_3224333442521978667250005
null
[ "Pd_iter1_Pd_1_mp-1186427_elastic_B222_dist03_8_2100_0" ]
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2023-12-01T22:57:35
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CO_9953300929534362443032716
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
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2023-12-01T17:58:06
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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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
Pd
A
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MD_1213582242930949697188121
2024-08-16T14:27:48
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2023-12-01T22:57:35
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CO_9961630106970960648902111
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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MD_1213582242930949697188121
2024-08-16T14:32:25
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2023-12-01T22:57:35
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CO_9963134452225664924845543
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd32
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MD_1213582242930949697188121
2024-08-16T15:41:14
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MD_8623581532269720749474932
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2023-12-01T22:57:35
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CO_9981447583005763389290039
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
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MD_1213582242930949697188121
2024-08-16T15:38:54
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MD_1086845055867124744315202
null
[ "Pd_iter1_Pd_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_dist03_7_6" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9989875793223992896809590
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/8d5bdb05
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DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0
Pd64
Pd
A
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DFT-PBE
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null
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MD_1213582242930949697188121
2024-08-16T14:31:08
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PO_2213722496459038665032879
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MD_1210149765697517309887518
null
[ "Pd_iter1_Pd_2_n-AzTtpB8GX6Rv7gu9K1KTBIkACv_elastic_B222_dist03_0_525_0" ]
[ "DS_g0sb0h7usqw7_0" ]
2023-12-01T22:57:35
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CO_9996305383569840442937919
23-Single-Element-DNPs_RSCDD_2023-Pd
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pd from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pd" ]
1
3,478
3,478
140,196
0
3,478
0
3,478
0
3,478
-158.91135
12,101.314813
0
2023-12-01T17:58:06
[ [ 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}
10.60732/8d5bdb05
2994911774059270670378424377814642525072873454860382972184404677795809752482386159057686702942140800605557237573413114025760093610213559709762043368167870
DS_g0sb0h7usqw7_0
23-Single-Element-DNPs_RSCDD_2023-Pd__Andolina-Saidi__DS_g0sb0h7usqw7_0