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

Dataset card Data Studio Files Community
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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_8972473288762560840401259
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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MD_1213582242930949697188121
2024-08-16T14:16:52
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MD_2096345489737508205541934
null
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2023-12-01T22:58:07
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CO_2524981267830078611074793
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
2024-08-16T14:37:50
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MD_4781419027403650273184564
null
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2023-12-01T22:58:06
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CO_4103443948758409407844026
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
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MD_1213582242930949697188121
2024-08-16T15:24:00
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MD_1086845055867124744315202
null
[ "Pt_iter1_2_5COO2H3XeXwKrq0BOxP3lzWgNkUY_elastic_B222_dist03_5_2" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_7229948477402652980051966
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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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt33
Pt
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MD_1213582242930949697188121
2024-08-16T15:09:26
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PO_9630042286814712090988129
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MD_3209829938723567883682128
null
[ "Pt_iter2_0_mp-126_interstitials_FCC2_db100_2100_4" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_5231276587271314569213505
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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MD_1213582242930949697188121
2024-08-16T14:24:05
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PO_1020397447086467645017293
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MD_2096345489737508205541934
null
[ "Pt_iter3_0_mp-126_elastic_B222_dist03_6_525_5" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_7925618958774534973807425
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
Pt16
Pt
A
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CO_5369382398511846500756014
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
2024-08-16T14:35:03
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2023-12-01T22:58:07
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CO_1025397408585248369285086
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
2024-08-16T14:41:00
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MD_1210149765697517309887518
null
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2023-12-01T22:58:07
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CO_2099509053134509130880803
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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2024-08-16T14:43:55
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CO_7028455401630354279780870
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
2024-08-16T15:22:52
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MD_4781419027403650273184564
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2023-12-01T22:58:07
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CO_7824815992376194496839356
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}
10.60732/49b97320
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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
2024-08-16T15:19:44
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2023-12-01T22:58:07
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CO_6451991914032027505533528
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
2024-08-16T14:34:18
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2023-12-01T22:58:06
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CO_1144412193771888712606128
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
2024-08-16T14:52:43
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MD_1210149765697517309887518
null
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2023-12-01T22:58:06
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CO_1208787673208715026759445
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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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
2024-08-16T14:19:51
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MD_1086845055867124744315202
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2023-12-01T22:58:06
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CO_6381326819201885379028156
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
2024-08-16T15:03:29
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_interstitials_FCC_interOh_13" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_9389976611081914123679448
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_4781419027403650273184564
null
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CO_3882913899220804753554378
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_8956182940275653111217839
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
2024-08-16T14:14:18
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MD_1086845055867124744315202
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[ "Pt_iter1_3_C9BvrCuSR5pUZ9Ec1SBqSvCjV04O_elastic_B222_dist03_11_8" ]
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2023-12-01T22:58:06
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CO_1120075610412302447101241
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
Pt
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MD_1213582242930949697188121
2024-08-16T14:59:14
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MD_4781419027403650273184564
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CO_6326202826233704934617811
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
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MD_1086845055867124744315202
null
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[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_1252204181078382421902498
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
Pt15
Pt
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CO_8785086159451019933132348
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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23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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CO_5781338892782226569749895
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_2063754080820186404470541
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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CO_7299111381515566117973657
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
2024-08-16T15:17:05
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PO_9672932472881359453781761
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MD_3209829938723567883682128
null
[ "Pt_iter3_0_mp-126_interstitials_FCC2_db100_2100_2" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_2908498257141018772962010
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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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
A
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[ "Pt" ]
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MD_1213582242930949697188121
2024-08-16T15:17:44
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_vacancies_Vac_0_34" ]
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2023-12-01T22:58:06
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CO_3203968764406938798786697
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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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
2024-08-16T15:14:02
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MD_3209829938723567883682128
null
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2023-12-01T22:58:06
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CO_9255395463430459414481000
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
2024-08-16T14:46:21
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MD_4781419027403650273184564
null
[ "Pt_iter1_0_mp-126_interstitials_FCC2_db111_3" ]
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2023-12-01T22:58:07
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CO_8157988879189789269660878
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
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CO_1257344735375822462374213
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
2024-08-16T15:09:15
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MD_1086845055867124744315202
null
[ "Pt_iter1_3_C9BvrCuSR5pUZ9Ec1SBqSvCjV04O_elastic_B222_dist03_9_2" ]
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2023-12-01T22:58:06
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CO_5435647823954772536089516
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
2024-08-16T14:39:20
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MD_4781419027403650273184564
null
[ "Pt_iter1_0_mp-126_elastic_B222_dist03_5_7" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_1230570289828716840529864
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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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T15:23:31
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PO_8972012711663356449711043
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_5_23" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_9805317420801789317065693
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
2024-08-16T14:42:41
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PO_4857856290170080703299289
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_8_20" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_9601859193612265505548213
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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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
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MD_1213582242930949697188121
2024-08-16T15:41:22
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MD_7739915350941659843248639
null
[ "Pt_iter2_2_5COO2H3XeXwKrq0BOxP3lzWgNkUY_elastic_B222_dist03_11_2100_6" ]
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2023-12-01T22:58:07
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CO_5462264466056143643438609
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
Pt7
Pt
A
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VASP
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MD_1213582242930949697188121
2024-08-16T14:13:37
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MD_7739915350941659843248639
null
[ "Pt_iter3_4_diamond_vacancies_Vac_0_2100_0" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_2670757536024916085256161
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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MD_1213582242930949697188121
2024-08-16T14:14:42
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PO_7589967518650431027891867
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MD_3209829938723567883682128
null
[ "Pt_iter2_0_mp-126_elastic_B222_dist03_10_2100_2" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_1633017688809018745123208
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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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
Pt15
Pt
A
[ 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78 ]
[ "Pt" ]
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1
15
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MD_1213582242930949697188121
2024-08-16T15:03:59
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MD_7739915350941659843248639
null
[ "Pt_iter2_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_vacancies_Vac_0_2100_6" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1180101640309162009604529
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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23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
2024-08-16T15:16:36
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PO_1301367575400797914205932
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_2_3" ]
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2023-12-01T22:58:06
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CO_1319165292095067082331906
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
2024-08-16T14:36:50
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CO_2567498635202899994487129
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
2024-08-16T15:24:52
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MD_1086845055867124744315202
null
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CO_5183970731583139256758831
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
2024-08-16T14:28:16
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PO_5940212175035470601219664
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_8_23" ]
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2023-12-01T22:58:06
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CO_9880174111146074326151546
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
2024-08-16T14:22:54
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MD_7739915350941659843248639
null
[ "Pt_iter3_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_elastic_B222_dist03_8_2100_7" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_8380651054068241905463365
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
2024-08-16T14:38:58
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PO_6644085112273830088820435
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_4_13" ]
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2023-12-01T22:58:06
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CO_5175623578768065326192977
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
Pt33
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MD_1213582242930949697188121
2024-08-16T15:35:29
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MD_4781419027403650273184564
null
[ "Pt_iter1_0_mp-126_interstitials_FCC2_crowdion_0" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_5121846971215956290621813
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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23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
Pt16
Pt
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CO_1957054723542019581652877
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
2024-08-16T14:26:31
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MD_7739915350941659843248639
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2023-12-01T22:58:06
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CO_9250443909745728109084974
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
2024-08-16T14:37:27
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_vacancies_Vac_0_30" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_7340190600614553848623708
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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CO_4518737671945192039276133
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
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CO_9893037894548381606497659
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
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null
[ "Pt_iter1_0_mp-126_elastic_B222_dist03_6_1" ]
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CO_2306823836400635843669436
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
2024-08-16T14:14:52
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PO_3269973259358865820175305
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MD_7739915350941659843248639
null
[ "Pt_iter2_2_5COO2H3XeXwKrq0BOxP3lzWgNkUY_elastic_B222_dist03_10_2100_2" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1227904782229098180689024
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
2024-08-16T15:38:36
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PO_9914291427850870655336054
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_10_6" ]
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2023-12-01T22:58:07
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CO_8927068696280934640268622
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
Pt16
Pt
A
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CO_8895625674581773424568881
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_7335029066107775726647789
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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2023-12-01T22:58:07
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CO_9766094087344691046196821
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
2024-08-16T14:25:47
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_vacancies_Vac_0_5" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_7923829585736830289567037
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
Pt31
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MD_1213582242930949697188121
2024-08-16T15:29:11
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PO_1332539081071010218836609
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MD_4781419027403650273184564
null
[ "Pt_iter1_0_mp-126_vacancies_Vac_0_4" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1166472749420611646566047
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 ] ]
[ 3 ]
2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/49b97320
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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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1
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CO_6911426161467738469170127
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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2024-08-16T14:54:38
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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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CO_2534094734610280920144162
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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23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0
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MD_1213582242930949697188121
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CO_1274814143687956099916158
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
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MD_1213582242930949697188121
2024-08-16T14:13:37
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MD_1210149765697517309887518
null
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2023-12-01T22:58:07
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CO_2673278183028818038166694
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
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MD_1213582242930949697188121
2024-08-16T14:57:08
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PO_1000972260015480710270365
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MD_1086845055867124744315202
null
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2023-12-01T22:58:06
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CO_6442255963542196822477903
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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2024-08-16T14:15:34
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CO_3418344479301874275917704
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
2024-08-16T14:53:10
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2023-12-01T22:58:06
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CO_3680798598691246746658250
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
2024-08-16T14:18:58
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MD_1086845055867124744315202
null
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2023-12-01T22:58:06
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CO_6280836337858670025720336
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_1146795142948788369205164
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
2024-08-16T14:12:46
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null
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2023-12-01T22:58:07
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CO_1133491721579539041421465
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
2024-08-16T14:14:50
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MD_1086845055867124744315202
null
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2023-12-01T22:58:06
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CO_1291382295078196691275867
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
2024-08-16T14:47:42
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CO_3477585177985600779877451
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
2024-08-16T15:15:23
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MD_1086845055867124744315202
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2023-12-01T22:58:07
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CO_1964389590824453539997953
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
2024-08-16T14:35:24
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PO_3492106858751839087240066
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MD_7739915350941659843248639
null
[ "Pt_iter2_2_5COO2H3XeXwKrq0BOxP3lzWgNkUY_elastic_B222_dist03_4_2100_2" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_1018497510412253725235007
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
2024-08-16T14:17:12
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PO_8583552247288657918531334
{"materials-project-id": "mp-126", "temperature": 2100, "hash": "3209829938723567883682128104627992266261517231725559418493446534811280053849958700494199933065908049152503028080749114784326135460689675105070357751722211", "id": "MD_3209829938723567883682128"}
MD_3209829938723567883682128
null
[ "Pt_iter3_0_mp-126_elastic_B222_dist03_6_2100_1" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_3971843734956056689887975
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}
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
2024-08-16T15:23:47
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PO_4311313478151968068599263
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_6_16" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_9348322707924921893357749
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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[ 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
[ 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 78 ]
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MD_1213582242930949697188121
2024-08-16T15:31:40
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MD_1086845055867124744315202
null
[ "Pt_iter1_1_cGAS2LRJaQh-bvTdqx4mGBiHwcBF_elastic_B222_dist03_5_0" ]
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2023-12-01T22:58:06
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CO_3187144394559747027478005
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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MD_1213582242930949697188121
2024-08-16T14:14:38
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PO_8329802460995575174711523
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MD_4781419027403650273184564
null
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2023-12-01T22:58:06
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CO_1207690735887843374877660
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
2024-08-16T15:16:09
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CO_5114068649074396839262500
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_8276979036448893749239677
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_8694701203710236387080750
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_7739915350941659843248639
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CO_6481909870947190984893448
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
2024-08-16T14:26:42
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CO_1000400993009517222597645
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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A
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MD_1213582242930949697188121
2024-08-16T15:24:31
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PO_1314261996035870012085192
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2023-12-01T22:58:07
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CO_4800824472437704967946244
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
2024-08-16T15:11:38
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PO_4371121594809599318702033
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_0_19" ]
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2023-12-01T22:58:07
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CO_2575614384217443171145779
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
2024-08-16T15:40:12
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PO_4699057638972893687648717
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_10_22" ]
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2023-12-01T22:58:06
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CO_9651542767416616617701637
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}
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
2024-08-16T14:46:38
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MD_1086845055867124744315202
null
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[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_1253223253294648076468609
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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MD_1213582242930949697188121
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MD_4781419027403650273184564
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CO_1813726956497975629958529
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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MD_1086845055867124744315202
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2023-12-01T22:58:06
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CO_5342347406353891016958970
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
2024-08-16T14:44:04
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PO_1088559906154671250167454
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MD_7739915350941659843248639
null
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2023-12-01T22:58:06
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CO_2380357649926326224800642
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
2024-08-16T15:08:51
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MD_1086845055867124744315202
null
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2023-12-01T22:58:06
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CO_3287814269627052404314781
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
2024-08-16T14:27:53
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PO_1329234067793645170962227
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MD_3209829938723567883682128
null
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2023-12-01T22:58:06
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CO_8230922539037372153763686
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
2024-08-16T15:04:03
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_vacancies_Vac_0_14" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_1082968814750800545999210
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
2024-08-16T15:03:24
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PO_6491668994203378765046509
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MD_4781419027403650273184564
null
[ "Pt_iter1_0_mp-126_interstitials_FCC2_interOh_5" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:07
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CO_4045682707210124175197641
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
2024-08-16T14:43:23
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_2_9" ]
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2023-12-01T22:58:06
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CO_5922119814533098108957661
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
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MD_3209829938723567883682128
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2023-12-01T22:58:07
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CO_5104499064465952551307028
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
2024-08-16T15:19:31
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PO_1314046154543741193483238
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MD_7739915350941659843248639
null
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2023-12-01T22:58:07
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CO_8894733544996129742995534
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
2024-08-16T15:02:43
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MD_4781419027403650273184564
null
[ "Pt_iter0_T525_0_mp-126_elastic_B222_dist03_11_14" ]
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2023-12-01T22:58:07
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CO_1177053107725469421063082
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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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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[ "Pt" ]
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DFT-PBE
null
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MD_1213582242930949697188121
2024-08-16T15:19:19
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PO_9562172550587295402114332
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MD_4781419027403650273184564
null
[ "Pt_iter0_T2100_0_mp-126_elastic_B222_dist03_2_2" ]
[ "DS_0zgz34a90a6i_0" ]
2023-12-01T22:58:06
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CO_1266740666539238186418939
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" ]
1
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62,152
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2,609
0
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 ] ]
[ 3 ]
2023
[ 1 ]
GPL-3.0-only
{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/49b97320
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DS_0zgz34a90a6i_0
23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0