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2023-12-01T22:52:18
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CO_1233793977639421082432153
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:01:29
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2023-12-01T22:52:18
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CO_6995797670943346175456380
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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CO_5450033487653508326483824
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
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[ "Ag_iter_all_Ag_iter0_315_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_8_10", "Ag_iter_all_Ag_iter0_315_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_8_22" ]
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2023-12-01T22:52:18
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CO_5655758086921027277559281
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:28:27
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PO_1105604051358563928303146
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_10_10", "Ag_iter_all_Ag_iter0_1260_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_10_23" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_3724674844327549425716163
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:17:30
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[ "Ag_iter_all_Ag_iter0_315_1_mp-124_elastic_B222_dist03_1_0", "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_1_7" ]
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2023-12-01T22:52:18
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CO_1004184388297736780063866
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:34:39
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PO_1179795161741155798805798
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter2_5_sc_elastic_B222_dist03_5_315_9" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_2567635452935490146039497
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag
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DFT-PBE
null
[ [ 0.00003206999826943502, 0.00016296000103466213, 0.000028410000595613383 ] ]
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MD_1213582242930949697188121
2024-08-16T14:42:28
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PO_3168819586152406895382127
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_6" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_5122496053791613735980411
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
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A
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MD_1213582242930949697188121
2024-08-16T14:58:17
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PO_8539456345567555668721058
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_interstitials_FCC2_db111_12" ]
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2023-12-01T22:52:18
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CO_9215679178659269142545670
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
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2024-08-16T15:07:18
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2023-12-01T22:52:18
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CO_2928074078393777013322426
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:23:32
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2023-12-01T22:52:18
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CO_4466637740148788755584378
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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2024-08-16T14:58:38
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2023-12-01T22:52:18
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CO_5017834651809771534266266
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:53:34
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter2_0_mp-989737_elastic_B222_dist03_9_315_7" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1447319447641869021159034
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
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MD_1213582242930949697188121
2024-08-16T14:46:27
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2023-12-01T22:52:18
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CO_1967026051306553493786165
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
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MD_1213582242930949697188121
2024-08-16T14:24:12
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter2_0_mp-989737_elastic_B222_dist03_8_315_7" ]
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2023-12-01T22:52:18
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CO_2387968368056389326488907
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:57:38
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PO_2536783836484789995895829
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_db111_315_6" ]
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2023-12-01T22:52:18
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CO_1248360624565988149301212
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
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MD_1213582242930949697188121
2024-08-16T14:53:27
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null
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2023-12-01T22:52:18
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CO_5213565116498173786084164
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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Ag
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MD_1213582242930949697188121
2024-08-16T15:39:33
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_315_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_12" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8530292268550733099878994
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:00:43
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_elastic_B222_dist03_6_13" ]
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2023-12-01T22:52:18
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CO_1021743068600727975956182
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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[ "Ag" ]
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CO_4775504542026462635535656
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2024-08-16T15:03:24
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MD_7937089555795707578009689
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2023-12-01T22:52:18
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CO_8656787013485027635432140
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag4
Ag
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2024-08-16T14:17:09
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PO_1220855431321257884318864
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MD_1132670352840213955900662
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2023-12-01T22:52:18
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CO_1614526160466039277200103
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:15:26
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PO_2794054478435946469488717
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MD_1132670352840213955900662
null
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2023-12-01T22:52:18
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CO_3890556130450370034729860
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:13:10
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PO_3490891568510304084508871
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_8_4" ]
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2023-12-01T22:52:18
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CO_1167645027270003583979048
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag64
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:31:03
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PO_1317174898105341422410092
{"temperature": 1260, "hash": "793708955579570757800968982051693420000843082157434399235740643094350109414342465319324642664231091423434192389540113951748090679376932895685941263591506", "id": "MD_7937089555795707578009689"}
MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_11_13" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8020798473488489764069820
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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3,795
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2023-12-01T17:52:28
[ [ 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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
[ 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47, 47 ]
[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T14:28:21
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MD_1132670352840213955900662
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[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_4_2" ]
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2023-12-01T22:52:18
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CO_7909474299617504768140478
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:13:03
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MD_1212537137353939262048417
null
[ "Ag_iter_all_Ag_iter2_3_mp-10597_elastic_B222_dist03_8_315_2" ]
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2023-12-01T22:52:18
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CO_9960541833781410901669715
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag31
Ag
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MD_1213582242930949697188121
2024-08-16T15:33:23
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MD_3607014462430280100943246
null
[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_vacancies_Vac_0_20" ]
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2023-12-01T22:52:18
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CO_6210763984257295692731135
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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
2024-08-16T14:15:31
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MD_7369907572514802664472459
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[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_8_12" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_2293248258902651319957802
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:18:56
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PO_5641867799460471645095822
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_elastic_B222_dist03_1_315_9" ]
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2023-12-01T22:52:18
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CO_1441970340246958733011557
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:26:22
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2023-12-01T22:52:18
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CO_3692314201396762440999581
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:36:44
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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CO_3728708535433349409789333
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:23:58
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2023-12-01T22:52:18
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CO_4944654618703336311616235
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
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MD_1213582242930949697188121
2024-08-16T15:21:26
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MD_7369907572514802664472459
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2023-12-01T22:52:18
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CO_1193867710890706655647901
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:15:47
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PO_5034044317037093004975609
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MD_1132670352840213955900662
null
[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_9_2" ]
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2023-12-01T22:52:18
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CO_9156389144912591834200112
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:47:03
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PO_7830693638393838859958824
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_interOh_315_8" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_6812268230671699016078988
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:13:49
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PO_1256333701011011200921827
{"materials-project-id": "mp-124", "temperature": 1260, "hash": "8328333280534599668480665244495013534205131916250553748395247603575458621133451557343901170867215808609131575955333758669127640608507517902470598063908496", "id": "MD_8328333280534599668480665"}
MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_elastic_B222_dist03_6_7" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1307319493873655404851619
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:57:02
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PO_1272554546842130001015410
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter0_1260_1_mp-124_interstitials_FCC2_db100_6" ]
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2023-12-01T22:52:18
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CO_1133420184993585559799704
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:19:44
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PO_1326068475498739935820189
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MD_3607014462430280100943246
null
[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_elastic_B222_dist03_6_9" ]
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2023-12-01T22:52:18
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CO_1081102583209653922726616
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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MD_1213582242930949697188121
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MD_3607014462430280100943246
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2023-12-01T22:52:18
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CO_5985549476766614876810067
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
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2023-12-01T22:52:18
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CO_8000142243338552956294290
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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2023-12-01T22:52:18
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CO_6199802235013709519034853
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:15:28
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2023-12-01T22:52:18
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CO_1054163496813010889488076
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:32:34
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_10" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_6773747846104925173616723
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:29:52
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PO_2207496476372569381974394
{"materials-project-id": "mp-124", "temperature": 315, "hash": "1901264063649552057980032765360091244306129156863244765520539936315517545718139405924156609694941144556195633664429638527201258218040275372883302651202181", "id": "MD_1901264063649552057980032"}
MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_db100_315_8" ]
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2023-12-01T22:52:18
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CO_1159109951147146245008261
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
Ag
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MD_1213582242930949697188121
2024-08-16T14:14:05
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MD_7369907572514802664472459
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[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_11_5" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_1319876296714235977311734
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag8
Ag
A
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MD_1213582242930949697188121
2024-08-16T15:36:42
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MD_7937089555795707578009689
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2023-12-01T22:52:18
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CO_6731921848890077359603834
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
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MD_1213582242930949697188121
2024-08-16T15:19:37
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MD_8328333280534599668480665
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[ "Ag_iter_all_Ag_iter2_1_mp-124_elastic_B222_dist03_4_1260_7" ]
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2023-12-01T22:52:18
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CO_1249003655066300076536344
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:09:53
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_elastic_B222_dist03_5_315_5" ]
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2023-12-01T22:52:18
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CO_7946270989386490036277326
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
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MD_1213582242930949697188121
2024-08-16T15:04:39
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{"materials-project-id": "mp-8566", "temperature": 1260, "hash": "3607014462430280100943246663438427879436346551450381038823753778253088670965950441956008500589099843141438118981671400718353914148461928019545349757294996", "id": "MD_3607014462430280100943246"}
MD_3607014462430280100943246
null
[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_elastic_B222_dist03_7_0" ]
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2023-12-01T22:52:18
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CO_7280106926942618559074395
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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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23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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CO_3876740318527253880052631
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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2024-08-16T15:15:42
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null
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2023-12-01T22:52:18
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CO_3906179628145696267091732
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:21:28
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2023-12-01T22:52:18
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CO_2751403000024073401346245
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:16:28
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_315_5_sc_elastic_B222_dist03_3_7" ]
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2023-12-01T22:52:18
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CO_6765244686254833937158446
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag24
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MD_1213582242930949697188121
2024-08-16T14:22:07
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter0_315_0_mp-989737_elastic_B222_dist03_3_7" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8561517161247176313101261
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:07:56
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MD_9448874345651185153904896
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2023-12-01T22:52:18
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CO_1084381206755880913756202
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:57:02
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[ "Ag_iter_all_Ag_iter0_315_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_0_6", "Ag_iter_all_Ag_iter0_1260_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_0_12" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_7721220991842009582303946
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag31
Ag
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MD_1213582242930949697188121
2024-08-16T14:36:02
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null
[ "Ag_iter_all_Ag_iter0_315_3_mp-10597_vacancies_Vac_0_14" ]
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2023-12-01T22:52:18
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CO_1182989952471245220520467
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:14:46
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MD_3607014462430280100943246
null
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2023-12-01T22:52:18
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CO_1208711794655923525067402
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:37:56
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MD_1132670352840213955900662
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2023-12-01T22:52:18
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CO_1246047904109610357111663
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:20:07
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MD_1303153961966051304389306
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2023-12-01T22:52:18
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CO_5560701986196510817094067
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:43:52
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MD_1901264063649552057980032
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2023-12-01T22:52:18
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CO_1165918319419867194840274
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:57:11
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MD_7937089555795707578009689
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2023-12-01T22:52:18
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CO_5146044876348382639511918
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T14:38:56
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PO_1382626107966463914053189
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_vacancies_Vac_0_1260_9" ]
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2023-12-01T22:52:18
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CO_4879519567249602325924832
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:47:01
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MD_1328667921261992109900361
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2023-12-01T22:52:18
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CO_1103054268445011276062626
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:56:25
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PO_7436748815663968882098462
{"materials-project-id": "mp-124", "temperature": 315, "hash": "1901264063649552057980032765360091244306129156863244765520539936315517545718139405924156609694941144556195633664429638527201258218040275372883302651202181", "id": "MD_1901264063649552057980032"}
MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_interstitials_FCC2_interOh_315_4" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8310190871458605946461631
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
[ [ 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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag64
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A
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2023-12-01T22:52:18
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CO_3079571659928358298272821
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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CO_1102283196844135841690950
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:33:24
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2023-12-01T22:52:18
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23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter0_1260_3_mp-10597_elastic_B222_dist03_11_14" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_4923953306329401230181989
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:49:59
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_4_19" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_6622145736848645482352214
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T15:16:53
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MD_1212537137353939262048417
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2023-12-01T22:52:18
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CO_1318612352742691328172237
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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
2024-08-16T14:33:16
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_elastic_B222_dist03_6_14" ]
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2023-12-01T22:52:18
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CO_1210640925880305437315568
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:32:49
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PO_1696509529203846763397850
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MD_1328667921261992109900361
null
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2023-12-01T22:52:18
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CO_1693700149345811599503897
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:18:44
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CO_1545997243863743551794140
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:32:25
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PO_1225146078470489765758960
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[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_0_12" ]
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2023-12-01T22:52:18
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CO_8355961549594984491340607
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag33
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2024-08-16T15:01:41
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MD_8328333280534599668480665
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2023-12-01T22:52:18
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CO_4782013577796546554341252
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:12:49
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PO_9109608161022025917914841
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MD_1132670352840213955900662
null
[ "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_11_14" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_8657604971759316849878074
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T14:17:49
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_elastic_B222_dist03_3_9" ]
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2023-12-01T22:52:18
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CO_1055761787062350051561166
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag64
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MD_1213582242930949697188121
2024-08-16T14:30:32
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PO_1068555207990217401876834
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MD_9448874345651185153904896
null
[ "Ag_iter_all_Ag_iter0_315_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_11_9" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_3469616820390413366371000
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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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}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T14:57:12
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[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_elastic_B222_dist03_8_7", "Ag_iter_all_Ag_iter0_315_2_mp-8566_elastic_B222_dist03_8_13" ]
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2023-12-01T22:52:18
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CO_3476502865256779309970017
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T14:26:09
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PO_7231643388117879864853944
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MD_7369907572514802664472459
null
[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_elastic_B222_dist03_0_7" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_6164545069706844550269064
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
10.60732/7cf58a2f
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DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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MD_1213582242930949697188121
2024-08-16T14:30:03
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MD_3607014462430280100943246
null
[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_elastic_B222_dist03_11_0" ]
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2023-12-01T22:52:18
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CO_5232615329522606372259872
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:31:46
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PO_5792091692278715630324230
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_315_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_5_0", "Ag_iter_all_Ag_iter0_1260_4_eI8KAHKA9NeQjf48uVhI3OmTw2An_elastic_B222_dist03_5_8" ]
[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
3250789350177527781456473818695307442221518135394149162827998375292016987840968948155541617529267172590519043986456726127809872083395924151023745557797114
CO_3250789350177527781456473
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
1
3,795
3,795
104,827
0
3,795
0
3,795
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3,795
-40.812777
7,781.558174
0
2023-12-01T17:52:28
[ [ 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}
10.60732/7cf58a2f
3938940090222256317111733741217524888628256684478029448602597292809705601036547133515339214611521546191650777367337278274175522512469735347507919045525440
DS_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag64
Ag
A
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[ "Ag" ]
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1
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2024-08-16T14:41:10
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MD_9448874345651185153904896
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2023-12-01T22:52:18
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CO_4563224354836841305687419
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:26:30
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PO_6682539135392484937360583
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MD_1901264063649552057980032
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[ "Ag_iter_all_Ag_iter0_315_1_mp-124_elastic_B222_dist03_6_4" ]
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2023-12-01T22:52:18
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CO_7637416626443503835279909
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag31
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MD_1213582242930949697188121
2024-08-16T15:10:58
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MD_3607014462430280100943246
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[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_vacancies_Vac_0_3" ]
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2023-12-01T22:52:18
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CO_8156076304250998504951920
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:49:20
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PO_2361867248574070898226864
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MD_1901264063649552057980032
null
[ "Ag_iter_all_Ag_iter0_315_1_mp-124_interstitials_FCC2_db110_7" ]
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2023-12-01T22:52:18
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CO_1280706460674789855706122
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
Ag
A
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CO_1272409117908054438049151
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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{'source-publication': 'https://doi.org/10.1039/D3DD00046J', 'source-data': 'https://github.com/saidigroup/23-Single-Element-DNPs', 'other': None}
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2024-08-16T14:38:11
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MD_1303153961966051304389306
null
[ "Ag_iter_all_Ag_iter0_315_0_mp-989737_elastic_8" ]
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2023-12-01T22:52:18
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CO_1279954823298645110395819
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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2023-12-01T22:52:18
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CO_6885992509515260815177552
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:25:00
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MD_8328333280534599668480665
null
[ "Ag_iter_all_Ag_iter2_1_mp-124_elastic_B222_dist03_2_1260_4" ]
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2023-12-01T22:52:18
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CO_3804363387426661173265054
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:16:05
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MD_8328333280534599668480665
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[ "Ag_iter_all_Ag_iter2_1_mp-124_elastic_B222_dist03_3_1260_6" ]
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2023-12-01T22:52:18
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CO_1149936676910855543327797
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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MD_1213582242930949697188121
2024-08-16T14:23:57
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2023-12-01T22:52:18
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CO_2493242642712532529464936
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T14:27:55
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PO_3819033680110800356520829
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[ "Ag_iter_all_Ag_iter0_1260_0_mp-989737_vacancies_Vac_0_10" ]
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2023-12-01T22:52:18
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CO_7097029661875086346993411
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag32
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2024-08-16T15:00:38
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MD_1132670352840213955900662
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2023-12-01T22:52:18
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CO_1275421255902243493478377
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
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MD_1213582242930949697188121
2024-08-16T15:11:47
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[ "DS_q4h7q8q0fnve_0" ]
2023-12-01T22:52:18
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CO_4434944994396332821716753
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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MD_1213582242930949697188121
2024-08-16T15:30:45
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MD_1328667921261992109900361
null
[ "Ag_iter_all_Ag_iter2_3_mp-10597_elastic_B222_dist03_7_1260_5" ]
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2023-12-01T22:52:18
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CO_1288430134376314745400187
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
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[ "Ag" ]
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MD_1213582242930949697188121
2024-08-16T14:49:02
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PO_1051244896046627712235326
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MD_3607014462430280100943246
null
[ "Ag_iter_all_Ag_iter0_1260_2_mp-8566_elastic_B222_dist03_5_3" ]
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2023-12-01T22:52:18
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CO_1270237468836780593365504
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.
[ "Ag" ]
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2023-12-01T17:52:28
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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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0
Ag
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VASP
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MD_1213582242930949697188121
2024-08-16T14:26:30
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PO_2681278004397303216971884
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MD_7937089555795707578009689
null
[ "Ag_iter_all_Ag_iter0_1260_5_sc_16" ]
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2023-12-01T22:52:18
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CO_3896640832406240137087200
23-Single-Element-DNPs_RSCDD_2023-Ag
[ "Christopher M. Andolina", "Wissam A. Saidi" ]
Configurations of Ag from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*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_q4h7q8q0fnve_0
23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0