colabfit/23-Single-Element-DNPs_RSCDD_2023-Zr

Zr17

Zr

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MD_1213582242930949697188121

2024-08-16T14:40:44

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_5939868121344233239253312

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

Zr8

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MD_1213582242930949697188121

2024-08-16T14:38:46

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CO_3896029498223880260704663

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

Zr16

Zr

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MD_1213582242930949697188121

2024-08-16T15:20:34

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null

[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_3_17" ]

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2023-12-01T23:00:32

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CO_7412217480235332846786997

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

2024-08-16T14:22:06

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MD_2794717748642297120678119

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_7_550_3" ]

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2023-12-01T23:00:32

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CO_5168533597487422813848427

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

2024-08-16T14:20:39

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_8270211137688464752948635

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

2024-08-16T15:15:29

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MD_5279706486609828620642959

null

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2023-12-01T23:00:32

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CO_1310668711373829363645899

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

Zr17

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MD_1213582242930949697188121

2024-08-16T15:38:01

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_interstitials_HCP2_interOhB_2200_3" ]

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2023-12-01T23:00:32

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CO_6383728739044573603054892

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

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MD_1213582242930949697188121

2024-08-16T14:19:43

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PO_2187137510348617594735282

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_crowdionB2_16" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6640087277456557707411155

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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[ 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

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MD_1213582242930949697188121

2024-08-16T14:41:46

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PO_1201505312778476917589618

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MD_9402372724898076044637979

null

[ "Zr_iter0_T550_4_mp-1056376_elastic_B222_dist03_8_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_2602012071637327518732621

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

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T15:37:47

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PO_1228538250256057911084850

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_9_14" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6517792670140492393208567

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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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 ]

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:53:37

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CO_5927074213200478510043909

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

2024-08-16T14:53:58

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MD_5279706486609828620642959

null

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2023-12-01T23:00:32

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CO_7808570840040015902272306

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

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MD_1213582242930949697188121

2024-08-16T15:06:45

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MD_5279706486609828620642959

null

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2023-12-01T23:00:32

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CO_1129369974578591127162202

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

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MD_1213582242930949697188121

2024-08-16T15:25:20

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PO_4336121415665224554179325

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MD_9402372724898076044637979

null

[ "Zr_iter0_T1300_4_mp-1056376_elastic_B222_dist03_5_3" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4283547016356007035410406

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

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MD_1213582242930949697188121

2024-08-16T15:00:24

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MD_1242681989026378489058465

null

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[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8587307177299462349714949

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

2024-08-16T15:17:04

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MD_6922568494354637749731581

null

[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_8_0" ]

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2023-12-01T23:00:32

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CO_1089323170342579759830833

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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A

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MD_1213582242930949697188121

2024-08-16T14:57:54

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_crowdionB_9" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_5703138987631166795370186

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

2024-08-16T14:37:24

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PO_1054520765692394340773585

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MD_3162313128594702633754619

null

[ "Zr_iter3_3_mp-41_elastic_B222_dist03_1_2200_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1322088402643107679419824

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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[ 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

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

2024-08-16T14:35:41

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PO_1074193719211435358770691

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MD_1055731924224023963324305

null

[ "Zr_iter2_0_mp-131_interstitials_HCP2_db_1" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1253890147948435272816115

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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[ 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

2024-08-16T14:15:17

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PO_6031843120991465376180613

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MD_5279706486609828620642959

null

[ "Zr_iter0_T550_3_mp-41_vacancies_Vac_0_23" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3328921561162803556372206

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

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MD_1213582242930949697188121

2024-08-16T15:15:05

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null

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[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1002279415183932860261969

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_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_1562258644942077662855787

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_5279706486609828620642959

null

[ "Zr_iter0_T2200_3_mp-41_elastic_B222_dist03_10_6" ]

[ "DS_h9w8v7289utq_0" ]

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CO_9824521831821786208952430

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

[ 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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null

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MD_1213582242930949697188121

2024-08-16T14:41:40

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PO_1182102394881442904388669

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_elastic_B222_dist03_9_2200_3" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1483428978768482110405800

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 ] ]

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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

Zr32

Zr

A

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[ "Zr" ]

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DFT-PBE

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null

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MD_1213582242930949697188121

2024-08-16T15:12:42

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PO_7127503776036068463522309

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MD_1023274440097845504342842

null

[ "Zr_iter3_2_mp-8635_elastic_B222_dist03_10_550_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_7125868620551735144970977

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

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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

Zr15

Zr

A

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

[ "Zr" ]

[ 1 ]

1

15

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null

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MD_1213582242930949697188121

2024-08-16T15:11:20

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PO_7254845511650482102400349

{"materials-project-id": "mp-41", "hash": "5279706486609828620642959527987689910687149551279576353390162926485379059112851258568003409206027061485309506246998059441849637254276873824071992781742380", "id": "MD_5279706486609828620642959"}

MD_5279706486609828620642959

null

[ "Zr_iter0_T550_3_mp-41_vacancies_Vac_0_47" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_2390969238015926501676718

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}

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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

2024-08-16T15:07:41

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MD_8829392809605781739714239

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_5_2200_7" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1111875245262342610290337

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

Zr2

Zr

A

[ 40, 40 ]

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DFT-PBE

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MD_1213582242930949697188121

2024-08-16T14:58:24

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MD_1053968927990176692110395

null

[ "Zr_iter1_3_mp-41_550_1" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:31

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CO_8676800298392481478289765

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 ]

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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

2024-08-16T14:55:46

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_0_9" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1736621668401243537625999

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 ]

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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

2024-08-16T14:43:18

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_2_12" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3855064313126698817786646

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 ]

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

2024-08-16T15:06:56

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_elastic_B222_dist03_0_2200_7" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8741969329298056817536546

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 ]

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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

Zr17

Zr

A

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[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:23:52

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PO_9717046711864241893817780

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_dbP2_17" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6872687749322662356375328

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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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

2024-08-16T14:55:48

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PO_5354703033283779429929125

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MD_5279706486609828620642959

null

[ "Zr_iter0_T550_3_mp-41_elastic_B222_dist03_6_15" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_2550830427773722418538883

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

Zr8

Zr

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MD_1213582242930949697188121

2024-08-16T14:40:08

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PO_5934495681066257572105685

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MD_8829392809605781739714239

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_2_2200_7" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6788219697825956800116530

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

Zr16

Zr

A

[ 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

2024-08-16T14:12:42

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PO_1089995610954248505459203

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MD_5279706486609828620642959

null

[ "Zr_iter2_3_mp-41_elastic_B222_dist03_2_1" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1080912023855683649840334

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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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

Zr8

Zr

A

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

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T15:32:05

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PO_1978740591979678150983816

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MD_2794717748642297120678119

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_9_550_6" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1306679783120782618411885

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

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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" ]

[ 1 ]

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MD_1213582242930949697188121

2024-08-16T14:49:47

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_8675327793244264937120616

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

2024-08-16T14:46:29

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MD_2794717748642297120678119

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2023-12-01T23:00:32

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CO_1079785181774025018998589

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

2024-08-16T14:56:37

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MD_2794717748642297120678119

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[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_8_550_7" ]

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2023-12-01T23:00:32

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CO_1313525498573671634504068

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

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MD_1213582242930949697188121

2024-08-16T15:10:38

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PO_1223808684502957085445231

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_crowdionP_2" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3232531357721689735102472

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

Zr7

Zr

A

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

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MD_1213582242930949697188121

2024-08-16T14:12:07

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PO_1250855344752114384714798

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MD_2794717748642297120678119

null

[ "Zr_iter3_4_mp-1056376_vacancies_Vac_0_550_2" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3015893006782004133716068

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

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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

A

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

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:33:44

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PO_1267293179304551632935974

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MD_5279706486609828620642959

null

[ "Zr_iter0_T550_3_mp-41_vacancies_Vac_0_33" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1042320529535377339678215

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

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10,022.893592

0

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

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

2024-08-16T15:17:47

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PO_3373562391472771342483318

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_elastic_B222_dist03_2_2200_6" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_9979193552245173989497463

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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[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:19:25

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_8_9" ]

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2023-12-01T23:00:31

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CO_5909611155854505644006677

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

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MD_1213582242930949697188121

2024-08-16T15:27:09

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PO_3683174436768250784832521

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MD_2794717748642297120678119

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_7_550_9" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3700064091231834216112533

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 ]

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:15:28

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MD_9402372724898076044637979

null

[ "Zr_iter0_T1300_4_mp-1056376_elastic_B222_dist03_4_4" ]

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2023-12-01T23:00:32

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CO_5105887602409624012758668

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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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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[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:40:13

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PO_8252461602820760594409068

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MD_1055731924224023963324305

null

[ "Zr_iter0_T1300_0_mp-131_elastic_B222_dist03_9_6" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_7866866644231248422871946

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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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

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CO_7959868114678434455433636

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

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CO_6818740510849596799468400

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

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CO_7263883837194670849909413

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

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null

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CO_7649548168588267513960274

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_1055731924224023963324305

null

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CO_2525521002891510479826897

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

2024-08-16T15:21:43

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MD_1055731924224023963324305

null

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[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1587100546383475082992171

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

Zr17

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MD_1213582242930949697188121

2024-08-16T15:23:13

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PO_8001769839257280789029847

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_2037577363397390210007807

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}

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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

2024-08-16T14:47:05

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PO_8515464544426161865884534

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MD_6922568494354637749731581

null

[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_1_18" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4686168523845495024707124

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

Zr17

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:07:13

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_interOh_13" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4717239236050169578204808

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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[ 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

2024-08-16T14:14:34

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PO_5514355851486952654686145

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MD_1055731924224023963324305

null

[ "Zr_iter0_T1300_0_mp-131_3", "Zr_iter2_0_mp-131_9" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3383650014048373215824995

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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{'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

2024-08-16T15:18:04

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_interstitials_HCP2_db_2200_0" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3127048799382968546771863

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

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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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MD_1213582242930949697188121

2024-08-16T14:45:03

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PO_6296198113545873290454125

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MD_1053968927990176692110395

null

[ "Zr_iter3_3_mp-41_vacancies_Vac_0_550_5" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4986271587627541380817850

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

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MD_1213582242930949697188121

2024-08-16T15:20:33

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PO_2213340588926978907850756

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_interstitials_HCP2_dbPP_2200_2" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_3306591484174067369185827

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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[ 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

2024-08-16T14:15:53

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_1310590971752284203466503

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

2024-08-16T14:54:56

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2023-12-01T23:00:32

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CO_8294284842999606054514745

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

2024-08-16T14:59:13

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PO_7506280616114958199878238

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_0_10" ]

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2023-12-01T23:00:32

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CO_1158643071859644851390929

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

2024-08-16T15:07:47

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2023-12-01T23:00:32

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CO_7072361369306129878173984

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

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MD_1213582242930949697188121

2024-08-16T14:41:36

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2023-12-01T23:00:32

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CO_4471264691378047579971053

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

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MD_1213582242930949697188121

2024-08-16T14:45:22

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null

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2023-12-01T23:00:32

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CO_6975452330200361157037432

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

2024-08-16T14:55:38

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MD_5279706486609828620642959

null

[ "Zr_iter0_T2200_3_mp-41_elastic_B222_dist03_1_9" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1296801532487584166359463

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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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

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MD_1213582242930949697188121

2024-08-16T14:25:13

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MD_6922568494354637749731581

null

[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_1_15" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8638867549021506962988547

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

Zr32

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:14:22

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MD_1023274440097845504342842

null

[ "Zr_iter3_2_mp-8635_elastic_B222_dist03_9_550_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1199050993328940739072287

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

Zr11

Zr

A

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

[ "Zr" ]

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1

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MD_1213582242930949697188121

2024-08-16T15:16:50

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CO_6529593959180456033666650

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

2024-08-16T15:25:29

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MD_9402372724898076044637979

null

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2023-12-01T23:00:32

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CO_1308100563710840310667763

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

2024-08-16T14:14:52

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MD_1242681989026378489058465

null

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2023-12-01T23:00:32

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CO_1253126890301770428763534

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

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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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2023-12-01T23:00:32

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CO_8643665204976131240751987

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

Zr17

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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_2267642071499229812337342

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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2024-08-16T15:07:57

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_interOhB_5" ]

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2023-12-01T23:00:32

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CO_1183303088374167897973660

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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23-Single-Element-DNPs_RSCDD_2023-Zr__Andolina-Saidi__DS_h9w8v7289utq_0

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MD_1213582242930949697188121

2024-08-16T15:29:40

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PO_9222136702159330840745583

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MD_2794717748642297120678119

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[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_10_550_4" ]

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2023-12-01T23:00:32

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CO_1195443813758149790295097

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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[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T15:24:47

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PO_4840091669691380072691883

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MD_6922568494354637749731581

null

[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_5_13" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4475830866976074495960028

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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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

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

[ "Zr" ]

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MD_1213582242930949697188121

2024-08-16T14:44:12

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null

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CO_8079313668101805078460277

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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2024-08-16T14:51:17

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_elastic_B222_dist03_7_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4409053550663116427981209

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

Zr17

Zr

A

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

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MD_1213582242930949697188121

2024-08-16T15:01:00

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_db_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_6944723750047888285100421

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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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

2024-08-16T15:17:27

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MD_8829392809605781739714239

null

[ "Zr_iter3_4_mp-1056376_elastic_B222_dist03_0_2200_9" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1492176883194358338915820

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

Zr

A

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MD_1213582242930949697188121

2024-08-16T14:46:13

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MD_9402372724898076044637979

null

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2023-12-01T23:00:32

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CO_8633611527483356172227569

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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[ 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

2024-08-16T14:35:07

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PO_1424252620966630603098760

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MD_1242681989026378489058465

null

[ "Zr_iter3_0_mp-131_elastic_B222_dist03_3_2200_9" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1281854069516662803280905

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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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

2024-08-16T15:26:53

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PO_1211253171183095709144700

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_2_6" ]

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2023-12-01T23:00:32

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CO_1265010000078798833644240

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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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

2024-08-16T14:59:23

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PO_8024648334548963550694716

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_8_0" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_9195677995845658063150565

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

Zr8

Zr

A

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

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MD_1213582242930949697188121

2024-08-16T15:06:52

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PO_1288163919256606412925304

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MD_9402372724898076044637979

null

[ "Zr_iter0_T1300_4_mp-1056376_elastic_B222_dist03_8_8" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1296214777249340881011319

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

Zr32

Zr

A

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[ "Zr" ]

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null

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MD_1213582242930949697188121

2024-08-16T14:21:24

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PO_1294762424572498680792744

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MD_6922568494354637749731581

null

[ "Zr_iter0_T2200_2_mp-8635_elastic_B222_dist03_0_14" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_5227767856705853358426462

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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[ 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

2024-08-16T14:42:41

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PO_4254202964109765039004320

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MD_5279706486609828620642959

null

[ "Zr_iter0_T2200_3_mp-41_elastic_B222_dist03_7_17" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_5785028700346012965825960

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 ]

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

2024-08-16T15:32:14

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PO_9018189295594639641875343

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MD_1055731924224023963324305

null

[ "Zr_iter0_T550_0_mp-131_interstitials_HCP2_dbP_11" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1095996694199691433155719

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

Zr32

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:24:38

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MD_6368844128943499733756333

null

[ "Zr_iter3_2_mp-8635_elastic_B222_dist03_7_2200_4" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1905645771593677618868059

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

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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

2024-08-16T15:30:09

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null

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2023-12-01T23:00:32

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CO_1070610113163720804228423

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

2024-08-16T14:22:47

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MD_1055731924224023963324305

null

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2023-12-01T23:00:32

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CO_5353047638739330395548577

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

2024-08-16T14:14:08

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PO_5659317326652020558652202

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_elastic_B222_dist03_11_0" ]

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2023-12-01T23:00:32

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CO_1197389740182350912626276

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

2024-08-16T14:42:57

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PO_5722842287632023142096424

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MD_9402372724898076044637979

null

[ "Zr_iter0_T2200_4_mp-1056376_elastic_B222_dist03_3_12" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_8829353826904560924401950

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

Zr32

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:20:27

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PO_5978986357076713415474086

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MD_6922568494354637749731581

null

[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_4_15" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_2992357500548763533722570

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

Zr32

Zr

A

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MD_1213582242930949697188121

2024-08-16T15:19:43

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PO_1445018692726647863409129

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MD_6922568494354637749731581

null

[ "Zr_iter0_T550_2_mp-8635_elastic_B222_dist03_11_18" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_4544192507189510152781568

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

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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

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CO_2853778133791718273918512

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

Zr17

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MD_1213582242930949697188121

2024-08-16T14:15:24

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MD_1055731924224023963324305

null

[ "Zr_iter0_T2200_0_mp-131_interstitials_HCP2_dbPP_18" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_2518586880990335590339423

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

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MD_6922568494354637749731581

null

[ "Zr_iter0_T1300_2_mp-8635_elastic_B222_dist03_3_1" ]

[ "DS_h9w8v7289utq_0" ]

2023-12-01T23:00:32

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CO_1268828733404757434571697

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