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23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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CO_9380965812503094105789812
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_7065181339972883482591947
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
2024-08-16T14:57:47
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MD_1086845055867124744315202
null
[ "Pt_iter1_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_elastic_B222_dist03_10_3" ]
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2023-12-01T22:58:06
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CO_1261668509337606270050458
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T14:30:40
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MD_2096345489737508205541934
null
[ "Pt_iter3_0_mp-126_elastic_B222_dist03_5_525_5" ]
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2023-12-01T22:58:07
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CO_1145131893505882699170674
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T15:12:33
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MD_2096345489737508205541934
null
[ "Pt_iter3_0_mp-126_elastic_B222_dist03_8_525_5" ]
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2023-12-01T22:58:06
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CO_7965741454117810438802192
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T15:37:07
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PO_2105719222464052030178527
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MD_3209829938723567883682128
null
[ "Pt_iter2_0_mp-126_elastic_B222_dist03_0_2100_7" ]
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2023-12-01T22:58:06
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CO_2742044869946374751708347
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
A
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CO_6446065735746641763716996
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
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2023-12-01T22:58:07
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CO_5567588669610231647364850
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
2024-08-16T15:15:31
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MD_1210149765697517309887518
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2023-12-01T22:58:06
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CO_1093689710119764688168899
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T14:36:42
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MD_4781419027403650273184564
null
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2023-12-01T22:58:06
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CO_1096216092207581807436866
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
2024-08-16T14:44:39
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MD_1210149765697517309887518
null
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[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_9560209632600646100482437
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:06:31
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MD_2096345489737508205541934
null
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CO_3178982112561583280205258
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:48:17
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PO_1306008530466893849535327
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MD_2096345489737508205541934
null
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2023-12-01T22:58:07
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CO_1145760112807075778345454
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt15
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:11:30
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PO_3850878229127978083200955
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MD_1086845055867124744315202
null
[ "Pt_iter1_2_5COO2H3XeXwKrq0BOxP3lzWgNkUY_vacancies_Vac_0_6" ]
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2023-12-01T22:58:07
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CO_6732917751037103213511940
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2023-12-01T17:58:14
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MD_1213582242930949697188121
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CO_4427379607332103591162396
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T15:00:39
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2023-12-01T22:58:06
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CO_2457147418414118873526320
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:29:56
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MD_1086845055867124744315202
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CO_6310855513803380051483284
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:31:23
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CO_9794005669162149550872120
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
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MD_1213582242930949697188121
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2023-12-01T22:58:07
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CO_9578059734364793808870962
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
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null
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23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
2024-08-16T15:31:40
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MD_1086845055867124744315202
null
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2023-12-01T22:58:07
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CO_2762820848717860169098056
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:28:57
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MD_1210149765697517309887518
null
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2023-12-01T22:58:07
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CO_9616716260637981266590017
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
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MD_1213582242930949697188121
2024-08-16T14:25:58
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_interstitials_FCC_interOh_18" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_8769190785722539539444923
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt31
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MD_1213582242930949697188121
2024-08-16T15:19:29
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PO_6086848644346115895000203
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_vacancies_Vac_0_33" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_3915321269431626302030969
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2,609
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7,864.95025
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2023-12-01T17:58:14
[ [ 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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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MD_1213582242930949697188121
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MD_1086845055867124744315202
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CO_1292922381858719304867867
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
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MD_1086845055867124744315202
null
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2023-12-01T22:58:06
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CO_1284897043251929110295233
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
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MD_4781419027403650273184564
null
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2023-12-01T22:58:07
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CO_5031077880926477890144192
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:20:15
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PO_8675274288510788513251772
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MD_1210149765697517309887518
null
[ "Pt_iter3_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_elastic_B222_dist03_10_525_10" ]
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2023-12-01T22:58:06
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CO_1026728297181527124508397
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:25:09
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PO_9588795734201349209820298
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MD_2096345489737508205541934
null
[ "Pt_iter2_0_mp-126_elastic_B222_dist03_1_525_7" ]
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2023-12-01T22:58:07
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CO_7869596727930165324126754
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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MD_1213582242930949697188121
2024-08-16T14:55:19
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MD_2096345489737508205541934
null
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CO_1322137547210010185157160
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:20:22
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PO_1095244416848830061473908
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MD_7739915350941659843248639
null
[ "Pt_iter2_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_elastic_B222_dist03_7_2100_7" ]
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2023-12-01T22:58:06
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CO_1131657289648092196298628
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
A
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VASP
DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:22:35
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PO_7641578705112082892061436
{"materials-project-id": "mp-126", "temperature": 525, "hash": "2096345489737508205541934178699042780547549270287393905333189394454713825888337501047188840763678879320402290436674410652384974635343169476430503158409500", "id": "MD_2096345489737508205541934"}
MD_2096345489737508205541934
null
[ "Pt_iter3_0_mp-126_interstitials_FCC2_db110_525_6" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1081791719415783755733373
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2,609
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7,864.95025
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2023-12-01T17:58:14
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:17:04
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_1_6" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_6829499848353923697986447
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:18:01
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PO_5169457403445167126604995
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_1_0" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_8578572013951842362381688
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2,609
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2023-12-01T17:58:14
[ [ 1, 1, 1 ] ]
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[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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MD_1213582242930949697188121
2024-08-16T14:40:51
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PO_5363602049700161270780718
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_6_21" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_8150975120710343926039229
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T15:29:31
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PO_1470701585901602731783506
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_3_14" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_4002146436143475451098783
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2,609
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2,609
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7,864.95025
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2023-12-01T17:58:14
[ [ 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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
[ 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78 ]
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2024-08-16T14:15:48
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CO_4030981102448903881481226
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:21:28
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CO_6924955650309919052511725
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
2024-08-16T14:44:23
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MD_7739915350941659843248639
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2023-12-01T22:58:07
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CO_6758660187934326954386256
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt7
Pt
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MD_1213582242930949697188121
2024-08-16T14:39:37
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MD_1086845055867124744315202
null
[ "Pt_iter1_4_diamond_vacancies_Vac_0_5" ]
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2023-12-01T22:58:06
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CO_6160337778390222352019155
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:34:50
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_4_21" ]
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2023-12-01T22:58:07
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CO_1327204241652694854226641
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T15:38:12
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CO_2595659783716084446505693
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:22:04
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MD_7739915350941659843248639
null
[ "Pt_iter3_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_elastic_B222_dist03_0_2100_5" ]
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2023-12-01T22:58:07
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CO_5417957327053570907871589
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:15:20
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PO_7396767288917181864118015
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MD_4781419027403650273184564
null
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2023-12-01T22:58:06
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CO_1169412170596982170061851
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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CO_1607580835250193518665133
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:49:55
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MD_1086845055867124744315202
null
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2023-12-01T22:58:07
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CO_1239809227004850869617067
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
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MD_4781419027403650273184564
null
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2023-12-01T22:58:06
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CO_3780197524713790798312516
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T14:45:15
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2023-12-01T22:58:06
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CO_4229985553757022752673971
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
2024-08-16T15:26:41
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MD_1210149765697517309887518
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2023-12-01T22:58:07
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CO_4129264586461541262370179
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
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MD_1213582242930949697188121
2024-08-16T14:42:18
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PO_4754132620815528160654772
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MD_7739915350941659843248639
null
[ "Pt_iter3_2_5COO2H3XeXwKrq0BOxP3lzWgNkUY_elastic_B222_dist03_7_2100_8" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_6879876531425451632748230
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_5837544856026697264949757
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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CO_4620391394460078053797204
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:37:16
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MD_7739915350941659843248639
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CO_2241383902097824950654373
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:30:37
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MD_1210149765697517309887518
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CO_1066878962831535835030521
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
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MD_1213582242930949697188121
2024-08-16T14:44:00
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MD_1086845055867124744315202
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2023-12-01T22:58:06
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CO_6885726703379265800178528
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:19:27
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PO_3884954896588835634669856
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_8_2" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_6059609164210590986598441
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
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MD_1213582242930949697188121
2024-08-16T15:09:02
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PO_4223602075768336476839071
{"materials-project-id": "mp-126", "temperature": 525, "hash": "2096345489737508205541934178699042780547549270287393905333189394454713825888337501047188840763678879320402290436674410652384974635343169476430503158409500", "id": "MD_2096345489737508205541934"}
MD_2096345489737508205541934
null
[ "Pt_iter3_0_mp-126_elastic_B222_dist03_10_525_1" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_7711229958206176489927797
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
[ [ 1, 1, 1 ] ]
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[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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CO_7570026860441772643206256
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
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2023-12-01T22:58:07
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CO_5484848409294722104059548
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
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CO_1114568202786805952680043
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:38:36
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MD_1086845055867124744315202
null
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CO_5933706217477167680998283
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:46:59
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MD_1210149765697517309887518
null
[ "Pt_iter2_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_elastic_B222_dist03_1_525_7" ]
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2023-12-01T22:58:06
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CO_9516407731589295093306633
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T14:20:34
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MD_2096345489737508205541934
null
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2023-12-01T22:58:06
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CO_8235637912959958806383184
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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CO_8159688618806803895750024
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
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MD_1213582242930949697188121
2024-08-16T14:54:36
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PO_1122492710646482695632189
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MD_7739915350941659843248639
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2023-12-01T22:58:06
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CO_2257469608804960671488785
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
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MD_1213582242930949697188121
2024-08-16T14:17:04
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PO_1141630015065792296324619
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MD_2096345489737508205541934
null
[ "Pt_iter3_0_mp-126_interstitials_FCC2_db100_525_2" ]
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2023-12-01T22:58:07
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CO_3881354285231893578201630
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
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MD_1213582242930949697188121
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MD_3209829938723567883682128
null
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CO_1139311165827302873108357
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:00:13
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PO_1003492802890432826911701
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MD_7739915350941659843248639
null
[ "Pt_iter3_3_C9BvrCuSR5pUZ9Ec1SBqSvCjV04O_elastic_B222_dist03_3_2100_5" ]
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2023-12-01T22:58:07
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CO_1042274995133974373623865
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:02:50
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PO_6143675701391090052361044
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MD_3209829938723567883682128
null
[ "Pt_iter3_0_mp-126_interstitials_FCC2_db100_2100_0" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1113897610666933579436439
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T14:40:22
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MD_4781419027403650273184564
null
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2023-12-01T22:58:07
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CO_2638677789504784894714253
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:28:27
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PO_2053835594450953252166622
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MD_7739915350941659843248639
null
[ "Pt_iter2_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_elastic_B222_dist03_8_2100_6" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_9144638650494068245147512
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
A
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MD_1213582242930949697188121
2024-08-16T14:59:34
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_interstitials_FCC_interTd_16" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_8780895658781335930641142
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:22:42
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PO_1253004844274174000065302
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_0_7" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1699551829037157811262299
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2023-12-01T17:58:14
[ [ 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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
A
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[ "Pt" ]
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MD_1213582242930949697188121
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CO_3995501886773817442685952
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
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MD_1213582242930949697188121
2024-08-16T15:22:07
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MD_1086845055867124744315202
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CO_3928193648476335100044924
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
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MD_1213582242930949697188121
2024-08-16T14:12:58
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MD_1086845055867124744315202
null
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CO_1163321944066951286587414
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1086845055867124744315202
null
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CO_2746521778338003497320167
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_4781419027403650273184564
null
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2023-12-01T22:58:07
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CO_3038218090620637771126465
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
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MD_1213582242930949697188121
2024-08-16T15:30:20
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MD_1086845055867124744315202
null
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2023-12-01T22:58:07
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CO_1072063853564064826980858
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
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MD_2096345489737508205541934
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2023-12-01T22:58:07
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CO_1158801745202344479605509
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
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MD_1213582242930949697188121
2024-08-16T15:15:47
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MD_7739915350941659843248639
null
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[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_4545002009711632013750956
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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2024-08-16T15:18:03
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MD_4781419027403650273184564
null
[ "Pt_iter1_0_mp-126_elastic_B222_dist03_9_7" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_4033761348484255464960542
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt31
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MD_1213582242930949697188121
2024-08-16T14:11:49
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PO_1074169740483472698390718
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_vacancies_Vac_0_22" ]
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2023-12-01T22:58:06
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CO_1187377994703383738359969
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
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MD_1213582242930949697188121
2024-08-16T14:38:26
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_10_14" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_5141104382891589004823294
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T15:39:46
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PO_7175330142393487389615941
{"materials-project-id": "mp-126", "temperature": 2100, "hash": "3209829938723567883682128104627992266261517231725559418493446534811280053849958700494199933065908049152503028080749114784326135460689675105070357751722211", "id": "MD_3209829938723567883682128"}
MD_3209829938723567883682128
null
[ "Pt_iter2_0_mp-126_vacancies_Vac_0_2100_3" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_9625279419868256679696677
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T14:39:44
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PO_8184389355428191666418498
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_11_0" ]
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2023-12-01T22:58:07
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CO_8478025242832741498606162
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2023-12-01T17:58:14
[ [ 1, 1, 1 ] ]
[ 3 ]
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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
A
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DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:40:54
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PO_4378017781023511122757233
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_interstitials_FCC_interOh_11" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_8854701629823454386423574
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt7
Pt
A
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DFT-PBE
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MD_1213582242930949697188121
2024-08-16T15:00:52
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PO_2270106107737512806604832
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MD_7739915350941659843248639
null
[ "Pt_iter3_4_diamond_vacancies_Vac_0_2100_4" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_8494712500801180123937529
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:14:17
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_8_4" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_6427723523313648019630115
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
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MD_1213582242930949697188121
2024-08-16T14:36:26
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PO_1308263194953860566793519
{"materials-project-id": "mp-126", "temperature": 525, "hash": "2096345489737508205541934178699042780547549270287393905333189394454713825888337501047188840763678879320402290436674410652384974635343169476430503158409500", "id": "MD_2096345489737508205541934"}
MD_2096345489737508205541934
null
[ "Pt_iter2_0_mp-126_interstitials_FCC2_db110_525_7" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1253972235449874123139284
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:27:03
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PO_8344754373237584270832643
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_10_9" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_9118198521120891690318641
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt31
Pt
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MD_1213582242930949697188121
2024-08-16T15:10:39
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_vacancies_Vac_0_17" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1280302440165872487842536
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
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MD_1213582242930949697188121
2024-08-16T15:39:43
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PO_5110879253255723426282804
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_6_24" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_8835723349776567631446651
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt32
Pt
A
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MD_1213582242930949697188121
2024-08-16T14:57:28
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MD_4781419027403650273184564
null
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2023-12-01T22:58:06
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CO_8679307518434354707611499
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T15:03:16
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MD_4781419027403650273184564
null
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2023-12-01T22:58:07
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CO_1154226512721968454996329
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:58:14
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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_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
A
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MD_1213582242930949697188121
2024-08-16T15:28:46
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MD_1210149765697517309887518
null
[ "Pt_iter3_3_C9BvrCuSR5pUZ9Ec1SBqSvCjV04O_elastic_B222_dist03_7_525_4" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1104471909040305454114925
23-Single-Element-DNPs_RSCDD_2023-Pt
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Pt from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Pt" ]
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2023-12-01T17:58:14
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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}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0