colabfit/23-Single-Element-DNPs_RSCDD_2023-Zr

Zr17

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:34:44

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_dbPP_3" ]

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2023-12-01T23:00:32

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CO_9388032038123698635708642

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:20:19

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_7021906926418912153693294

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr11

Zr

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MD_1213582242930949697188121

2024-08-16T14:58:18

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PO_5615124987964922149671751

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MD_2978268964833510307558018

null

[ "Zr_iter0_T2200_1_mp-1077723_vacancies_Vac_0_15" ]

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2023-12-01T23:00:32

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CO_1105026841665615125420330

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

Zr

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2024-08-16T14:23:02

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CO_7704313474361149389787315

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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2024-08-16T14:49:02

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2023-12-01T23:00:32

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CO_1524441233739191283437974

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:58:10

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MD_9402372724898076044637979

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CO_4590497129248226894643003

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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10.60732/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:17:02

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2023-12-01T23:00:32

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CO_4414917290359962295064093

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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

2024-08-16T14:19:11

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null

[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_4_15" ]

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2023-12-01T23:00:32

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CO_7236291353503653217160796

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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2024-08-16T15:30:14

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2023-12-01T23:00:32

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CO_8737586146992175697825476

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

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MD_1213582242930949697188121

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null

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CO_5418648378811357662439142

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

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MD_1242681989026378489058465

null

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2023-12-01T23:00:32

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CO_1124225887430147385504975

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:45:30

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_11_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8131126744288894771196981

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr15

Zr

A

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CO_5092068477381121341051855

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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MD_1213582242930949697188121

2024-08-16T14:12:44

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null

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CO_3444713632549971044631421

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

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MD_6922568494354637749731581

null

[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_9_9" ]

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2023-12-01T23:00:32

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CO_1097345918133105378685334

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr31

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CO_1222508346393959312427101

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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MD_1213582242930949697188121

2024-08-16T14:21:33

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MD_3162313128594702633754619

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2023-12-01T23:00:32

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CO_7229719577510827779336072

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr11

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MD_1213582242930949697188121

2024-08-16T14:38:14

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PO_2403176741679330675305949

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MD_2978268964833510307558018

null

[ "Zr_iter0_T2200_1_mp-1077723_vacancies_Vac_0_3" ]

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2023-12-01T23:00:32

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CO_1318001997752839019628569

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

Zr

A

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[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T15:19:40

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PO_2266415809736120993775403

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MD_8829392809605781739714239

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_10_2200_0" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6997151323373112220194136

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:31:18

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PO_2766029037368099547393751

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MD_6922568494354637749731581

null

[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_0_13" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3068304450864124000169976

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr32

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MD_1213582242930949697188121

2024-08-16T14:17:12

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2023-12-01T23:00:32

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CO_2203460388906612593501305

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:22:06

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_interTdB_10" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_5719335373256211929552587

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:29:40

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MD_6922568494354637749731581

null

[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_0_5" ]

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2023-12-01T23:00:32

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CO_9968562212765597961452890

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:37:23

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MD_1242681989026378489058465

null

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[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1175584302509582949391966

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr15

Zr

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MD_1213582242930949697188121

2024-08-16T14:14:14

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MD_3162313128594702633754619

null

[ "Zr_iter3_3_mp-41_vacancies_Vac_0_2200_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_2778998230374945224325253

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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10,022.893592

0

2023-12-01T18:03:07

[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr2

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:43:52

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MD_3162313128594702633754619

null

[ "Zr_iter1_3_mp-41_2200_3" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:31

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CO_7364996468118289720826416

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

[ [ 1, 1, 1 ] ]

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2023

[ 1 ]

GPL-3.0-only

{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}

10.60732/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:18:11

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PO_2209164963447719207219419

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_dbP2_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:31

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CO_5386541514173062399665651

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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[ 3 ]

2023

[ 1 ]

GPL-3.0-only

{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}

10.60732/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr15

Zr

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MD_1213582242930949697188121

2024-08-16T14:15:47

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MD_5279706486609828620642959

null

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2023-12-01T23:00:32

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CO_4906006629946735447357630

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

[ [ 1, 1, 1 ] ]

[ 3 ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr2

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:39:39

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PO_3970198697200802311441625

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MD_1055731924224023963324305

null

[ "Zr_iter0_T1300_0_mp-131_0", "Zr_iter2_0_mp-131_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_5713937287102296843175360

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

Zr

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MD_1213582242930949697188121

2024-08-16T14:54:41

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MD_9402372724898076044637979

null

[ "Zr_iter0_T1300_4_mp-1056376_elastic_B222_dist03_9_0" ]

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2023-12-01T23:00:32

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CO_3470565312546180652472316

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

[ [ 1, 1, 1 ] ]

[ 3 ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr32

Zr

A

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[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:38:39

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MD_1023274440097845504342842

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[ "Zr_iter3_2_mp-8635_elastic_B222_dist03_11_550_4" ]

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2023-12-01T23:00:32

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CO_1719056616762223456714324

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:24:40

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PO_1256129348806605113317138

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MD_1053968927990176692110395

null

[ "Zr_iter3_3_mp-41_elastic_B222_dist03_9_550_3" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_9754421378959680551960905

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr7

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MD_1213582242930949697188121

2024-08-16T14:52:50

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PO_9757622616006665587123785

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_vacancies_Vac_0_5" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1453104666299595713354834

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

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MD_1213582242930949697188121

2024-08-16T15:24:22

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_elastic_B222_dist03_6_2200_6" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1278503750700941411829596

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:20:38

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MD_6922568494354637749731581

null

[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_6_4" ]

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2023-12-01T23:00:32

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CO_7725189484284924930622226

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

[ 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40 ]

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T15:23:20

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MD_5279706486609828620642959

null

[ "Zr_iter0_T2200_3_mp-41_elastic_B222_dist03_7_16" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6222084828807619740518178

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

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MD_1213582242930949697188121

2024-08-16T14:34:01

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null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_7_12" ]

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2023-12-01T23:00:32

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CO_1039778481288934574737470

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:34:59

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MD_1055731924224023963324305

null

[ "Zr_iter2_0_mp-131_interstitials_HCP2_dbB_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_2062628800457478050421244

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:05:09

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MD_5279706486609828620642959

null

[ "Zr_iter0_T2200_3_mp-41_elastic_B222_dist03_4_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8440440158632403423311971

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:14:13

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_9_1" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1121387755700194063542505

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:01:38

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null

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2023-12-01T23:00:32

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CO_6365233053622871965744506

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

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MD_1213582242930949697188121

2024-08-16T14:33:16

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MD_1055731924224023963324305

null

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[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1174798662203727159747905

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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10.60732/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:37:27

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PO_7888894131192905697036209

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MD_8829392809605781739714239

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_7_2200_6" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3935166240855105192533483

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

Zr

A

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2023-12-01T23:00:32

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CO_3640414962649880333771297

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:43:36

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null

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2023-12-01T23:00:32

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CO_9169075283068437043933118

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

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MD_1213582242930949697188121

2024-08-16T14:18:19

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MD_9402372724898076044637979

null

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2023-12-01T23:00:32

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CO_2717717846181928221587747

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

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MD_1213582242930949697188121

2024-08-16T15:37:31

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PO_1340220645808289508744434

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MD_1055731924224023963324305

null

[ "Zr_iter0_T1300_0_mp-131_interstitials_HCP2_dbP_4", "Zr_iter0_T1300_0_mp-131_interstitials_HCP2_dbP_12" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_7893238361310155420527393

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:02:34

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PO_1179617308674515030624242

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MD_6922568494354637749731581

null

[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_10_13" ]

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2023-12-01T23:00:32

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CO_7862877423624010387211024

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

[ 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40 ]

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MD_1213582242930949697188121

2024-08-16T14:59:46

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PO_1237075778214253318409685

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_0_1" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4042132534600598869081107

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

[ [ 1, 1, 1 ] ]

[ 3 ]

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[ 1 ]

GPL-3.0-only

{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}

10.60732/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:02:46

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MD_5279706486609828620642959

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2023-12-01T23:00:32

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CO_6099506378622638986336190

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}

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MD_1213582242930949697188121

2024-08-16T15:24:02

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null

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CO_3331796001242896557037081

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr15

Zr

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MD_1213582242930949697188121

2024-08-16T14:18:24

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_vacancies_Vac_0_2200_3" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3146570590562771344176668

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

Zr

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MD_1213582242930949697188121

2024-08-16T14:16:13

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PO_9715734564679325548894439

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_interstitials_HCP2_db_2200_9" ]

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2023-12-01T23:00:32

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CO_1230634733002507413988345

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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[ 3 ]

2023

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GPL-3.0-only

{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}

10.60732/efb626b6

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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:24:57

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_4_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6304616800118938935434517

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

Zr

A

[ 40, 40, 40, 40, 40, 40, 40, 40 ]

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MD_1213582242930949697188121

2024-08-16T14:20:18

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PO_1252990780318916685825974

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MD_8829392809605781739714239

null

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2023-12-01T23:00:32

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CO_6087696038020884540014202

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

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MD_1213582242930949697188121

2024-08-16T15:15:33

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PO_3300901772229081839104885

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MD_1055731924224023963324305

null

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[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_9371302821673102997394627

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

Zr

A

[ 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40 ]

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:57:08

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_2438506103535752624017411

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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

2024-08-16T14:38:58

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MD_2794717748642297120678119

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2023-12-01T23:00:32

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CO_3992866120587368065705405

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:17:42

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PO_1015697131300641176963856

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MD_3162313128594702633754619

null

[ "Zr_iter3_3_mp-41_elastic_B222_dist03_0_2200_1" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6967508039797685386296426

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:32:43

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_10_5" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_9980852191253496798283043

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:36:40

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PO_5818230197189939092522511

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MD_1023274440097845504342842

null

[ "Zr_iter3_2_mp-8635_elastic_B222_dist03_9_550_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_7518904023018412578523454

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr32

Zr

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[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T15:20:02

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MD_6922568494354637749731581

null

[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_9_14" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1946165932587200553443939

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:56:38

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MD_9402372724898076044637979

null

[ "Zr_iter2_4_mp-1056376_elastic_B222_dist03_5_4" ]

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2023-12-01T23:00:32

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CO_1593930253548450562619157

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:42:54

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PO_1340702441812923677595545

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MD_1055731924224023963324305

null

[ "Zr_iter0_T1300_0_mp-131_elastic_B222_dist03_10_2" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_5650849570543418146458812

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:29:03

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PO_6872556492942068675820799

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_3_2" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8984833628509864766890715

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:46:53

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_1124015452800058174343347

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

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MD_1213582242930949697188121

2024-08-16T14:42:11

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_db_12" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8784859061182758307785436

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

[ 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40 ]

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MD_1213582242930949697188121

2024-08-16T14:14:26

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PO_7981168977348250343568953

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MD_5279706486609828620642959

null

[ "Zr_iter0_T550_3_mp-41_elastic_B222_dist03_5_3" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1053489461033671496586950

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:15:14

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CO_9556850870564607957654136

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:50:49

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_4_1" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4176684833275931609584148

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr32

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MD_1213582242930949697188121

2024-08-16T14:17:25

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MD_6922568494354637749731581

null

[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_9_18" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4625679188861822730473445

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr32

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MD_1213582242930949697188121

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MD_6922568494354637749731581

null

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2023-12-01T23:00:32

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CO_6668452001492841531768436

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr15

Zr

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MD_1213582242930949697188121

2024-08-16T15:10:03

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MD_5279706486609828620642959

null

[ "Zr_iter0_T550_3_mp-41_vacancies_Vac_0_131" ]

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2023-12-01T23:00:32

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CO_3502313380361221465667614

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

[ [ 1, 1, 1 ] ]

[ 3 ]

2023

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GPL-3.0-only

{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}

10.60732/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

[ 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40 ]

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T15:01:05

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PO_9127485950215749382894339

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MD_3162313128594702633754619

null

[ "Zr_iter3_3_mp-41_elastic_B222_dist03_5_2200_3" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1246328691540849594491949

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:55:43

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MD_9402372724898076044637979

null

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2023-12-01T23:00:32

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CO_6111497492633529238556136

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:24:24

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PO_9495229348618854847847478

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MD_1265425156488878603940539

null

[ "Zr_iter3_0_mp-131_interstitials_HCP2_crowdionP_550_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8628613227695589421435377

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr32

Zr

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MD_1213582242930949697188121

2024-08-16T15:04:08

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PO_1006793413264153852118516

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MD_6922568494354637749731581

null

[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_6_15" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6033643313056644331244015

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

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[ 3 ]

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr15

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:22:42

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PO_5832206653810035393790917

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null

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CO_7420179074579220160609000

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr15

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:04:12

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MD_1055731924224023963324305

null

[ "Zr_iter2_0_mp-131_vacancies_Vac_0_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1291249821854465742040629

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:00:31

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PO_1630939901998990983546897

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MD_3162313128594702633754619

null

[ "Zr_iter3_3_mp-41_elastic_B222_dist03_5_2200_0" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1086153662258512858468086

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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CO_6335841605279731082848518

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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MD_1213582242930949697188121

2024-08-16T15:09:11

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[ "Zr_iter3_3_mp-41_elastic_B222_dist03_1_2200_7" ]

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2023-12-01T23:00:32

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CO_7205074268994004886395842

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

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MD_6922568494354637749731581

null

[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_5_11" ]

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2023-12-01T23:00:32

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CO_5020240574582794239553493

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:22:13

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MD_6922568494354637749731581

null

[ "Zr_iter0_T1300_2_mp-8635_elastic_B222_dist03_4_9" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6100113500188482363150701

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr32

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MD_1213582242930949697188121

2024-08-16T14:37:04

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MD_6922568494354637749731581

null

[ "Zr_iter0_T1300_2_mp-8635_elastic_B222_dist03_5_0" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:31

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CO_1049559173647742873564496

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

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2023-12-01T18:03:07

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[ 3 ]

2023

[ 1 ]

GPL-3.0-only

{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}

10.60732/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:24:37

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MD_3162313128594702633754619

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2023-12-01T23:00:32

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CO_7893672912108610948005515

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T14:18:37

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_crowdionB2_0" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1295771426598883736852987

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:12:30

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PO_2159436410653280571250577

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_0_5" ]

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2023-12-01T23:00:32

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CO_1314010850480483349733007

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:10:05

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PO_1193953842630366061591102

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MD_2794717748642297120678119

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_10_550_3" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1783933069518241432645773

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:12:16

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MD_5279706486609828620642959

null

[ "Zr_iter2_3_mp-41_elastic_B222_dist03_2_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1316898676741018180872726

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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null

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MD_1213582242930949697188121

2024-08-16T14:35:52

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PO_7918294947177878928683810

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MD_9402372724898076044637979

null

[ "Zr_iter2_4_mp-1056376_5", "Zr_iter0_T1300_4_mp-1056376_7" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:31

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CO_4844766825160225502740300

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:38:25

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PO_1289931109725043557041787

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_dbP_17" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1227234097446189607215613

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

[ [ 1, 1, 1 ] ]

[ 3 ]

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[ 1 ]

GPL-3.0-only

{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}

10.60732/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr8

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:32:25

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PO_4562114380066300360161002

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_9_6" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1132126990537432354777434

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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2023-12-01T18:03:07

[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr16

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:20:54

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PO_1077057790872297556901300

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MD_3162313128594702633754619

null

[ "Zr_iter3_3_mp-41_elastic_B222_dist03_4_2200_2" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6381012406533647398067785

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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0

2023-12-01T18:03:07

[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

Zr

A

[ 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40 ]

[ "Zr" ]

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1

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MD_1213582242930949697188121

2024-08-16T14:36:02

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PO_1600081383423217519387582

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_db_0" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1926056932067820482665366

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

1

4,730

81,165

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4,730

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4,730

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4,730

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10,022.893592

0

2023-12-01T18:03:07

[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr2

Zr

A

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DFT-PBE

null

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MD_1213582242930949697188121

2024-08-16T14:25:18

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PO_6595573147550980322068107

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MD_5279706486609828620642959

null

[ "Zr_iter2_3_mp-41_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6402950671910923892459220

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

1

4,730

81,165

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10,022.893592

0

2023-12-01T18:03:07

[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr

A

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DFT-PBE

null

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null

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MD_1213582242930949697188121

2024-08-16T14:49:27

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2023-12-01T23:00:31

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CO_3690509367005533206381866

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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

2024-08-16T14:17:14

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MD_5279706486609828620642959

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[ "Zr_iter0_T550_3_mp-41_elastic_B222_dist03_3_7" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4520631070647559038091511

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

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null

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2023-12-01T23:00:32

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CO_2701197388356398657642457

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

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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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

Zr17

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MD_1213582242930949697188121

2024-08-16T15:39:27

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PO_4564655374503939151042738

{"materials-project-id": "mp-131", "hash": "10557319242240239633243052075157509552013768715293155287413313665243709901949932522557582446835036231123736140426577800868669611783334574683439255201297053", "id": "MD_1055731924224023963324305"}

MD_1055731924224023963324305

null

[ "Zr_iter2_0_mp-131_interstitials_HCP2_dbB_2" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_9935748710528435458602915

23-Single-Element-DNPs_RSCDD_2023-Zr

[ "Christopher M. Andolina", "Wissam A. Saidi" ]

Configurations of Zr from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

[ "Zr" ]

1

4,730

81,165

0

4,730

0

4,730

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4,730

-129.536477

10,022.893592

0

2023-12-01T18:03:07

[ [ 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/efb626b6

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DS_h9w8v7289utq_0

23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0