Datasets:
Dataset Viewer
chemical_formula_hill
string | chemical_formula_reduced
string | chemical_formula_anonymous
string | atomic_numbers
sequence | elements
sequence | elements_ratios
sequence | nelements
int32 | nsites
int32 | cell
sequence | positions
sequence | pbc
sequence | dimension_types
sequence | nperiodic_dimensions
int32 | structure_hash
string | multiplicity
int32 | software
string | method
string | adsorption_energy
float64 | atomic_forces
sequence | atomization_energy
float64 | cauchy_stress
sequence | cauchy_stress_volume_normalized
bool | electronic_band_gap
float64 | electronic_band_gap_type
string | energy
float64 | formation_energy
float64 | max_force_norm
float64 | mean_force_norm
float64 | property_object_metadata
string | property_object_metadata_id
string | property_object_last_modified
timestamp[ns] | property_object_hash
string | property_object_id
string | configuration_metadata
string | configuration_metadata_id
string | configuration_labels
sequence | configuration_names
sequence | configuration_dataset_ids
sequence | configuration_last_modified
timestamp[ns] | configuration_hash
string | configuration_id
string | dataset_name
string | dataset_authors
sequence | dataset_description
string | dataset_elements
sequence | dataset_nelements
int32 | dataset_nproperty_objects
int64 | dataset_nconfigurations
int32 | dataset_nsites
int64 | dataset_adsorption_energy_count
int64 | dataset_atomic_forces_count
int64 | dataset_atomization_energy_count
int64 | dataset_cauchy_stress_count
int64 | dataset_electronic_band_gap_count
int64 | dataset_energy_count
int64 | dataset_energy_mean
float64 | dataset_energy_variance
float64 | dataset_formation_energy_count
int64 | dataset_last_modified
timestamp[ns] | dataset_dimension_types
sequence | dataset_nperiodic_dimensions
sequence | dataset_publication_year
string | dataset_total_elements_ratios
sequence | dataset_license
string | dataset_links
string | dataset_doi
string | dataset_hash
string | dataset_id
string | dataset_extended_id
string |
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VASP
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DFT-PBE
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
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MD_6206330277285791203846415
| 2024-08-16T14:13:02 |
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PO_7409648884415842606103371
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[
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[
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CO_1000075266527108307079892
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HfO2_DPGEN_PRB_2021
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[
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Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
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"O"
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2023
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
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DS_qgi1kbtdzwmm_0
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HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
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Hf32O64
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HfO2
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
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MD_6206330277285791203846415
| 2024-08-16T14:14:28 |
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PO_7877732388323021204373434
| null | null | null |
[
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[
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] | 2023-12-02T02:53:06 |
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CO_1000118490218717135214864
|
HfO2_DPGEN_PRB_2021
|
[
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"Yuzhi Zhang",
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"Shi Liu"
] |
Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
[
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3
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2023
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
|
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DS_qgi1kbtdzwmm_0
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HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
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Hf32O64
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HfO2
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A2B
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DFT-PBE
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
|
MD_6206330277285791203846415
| 2024-08-16T14:12:36 |
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|
PO_7794126414850017699745262
| null | null | null |
[
"sys.001_set.000_577"
] |
[
"DS_qgi1kbtdzwmm_0"
] | 2023-12-02T02:53:06 |
10001221491202708911890803461925749587065259181423602667858668386250325665684652877999301364236489395813163761424816913090065867907980347870243579171511266
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CO_1000122149120270891189080
|
HfO2_DPGEN_PRB_2021
|
[
"Jing Wu",
"Yuzhi Zhang",
"Linfeng Zhang",
"Shi Liu"
] |
Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
[
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1,
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1
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] |
[
3
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2023
|
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
|
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|
DS_qgi1kbtdzwmm_0
|
HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
|
Hf32O64
|
HfO2
|
A2B
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
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MD_6206330277285791203846415
| 2024-08-16T15:30:25 |
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PO_3962818939837927692324577
| null | null | null |
[
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[
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] | 2023-12-02T02:53:07 |
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CO_1000583030033675338189489
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HfO2_DPGEN_PRB_2021
|
[
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Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
[
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3
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2023
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
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DS_qgi1kbtdzwmm_0
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HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
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Hf32O64
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HfO2
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
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MD_6206330277285791203846415
| 2024-08-16T14:14:14 |
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PO_3459881531247393277473110
| null | null | null |
[
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[
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] | 2023-12-02T02:53:08 |
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CO_1000958482335287789667566
|
HfO2_DPGEN_PRB_2021
|
[
"Jing Wu",
"Yuzhi Zhang",
"Linfeng Zhang",
"Shi Liu"
] |
Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
[
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[
3
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2023
|
[
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
|
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|
DS_qgi1kbtdzwmm_0
|
HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
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Hf32O64
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HfO2
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A2B
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MD_6206330277285791203846415
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[
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[
"DS_qgi1kbtdzwmm_0"
] | 2023-12-02T02:53:07 |
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|
CO_1001183807838181002178992
|
HfO2_DPGEN_PRB_2021
|
[
"Jing Wu",
"Yuzhi Zhang",
"Linfeng Zhang",
"Shi Liu"
] |
Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
[
[
1,
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1
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[
3
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2023
|
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
|
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|
DS_qgi1kbtdzwmm_0
|
HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
|
Hf32O64
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HfO2
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A2B
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DFT-PBE
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MD_6206330277285791203846415
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PO_1079606631325930993781741
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[
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[
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CO_1001631444505219530120233
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HfO2_DPGEN_PRB_2021
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[
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Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
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2023
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
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DS_qgi1kbtdzwmm_0
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HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
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Hf32O64
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HfO2
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DFT-PBE
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MD_6206330277285791203846415
| 2024-08-16T14:50:25 |
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PO_3897672612360387527285616
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[
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[
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CO_1002539822284142060379249
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HfO2_DPGEN_PRB_2021
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[
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"Yuzhi Zhang",
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"Shi Liu"
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Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
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3
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2023
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
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DS_qgi1kbtdzwmm_0
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HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
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Hf32O64
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HfO2
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A2B
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DFT-PBE
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
|
MD_6206330277285791203846415
| 2024-08-16T14:13:48 |
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PO_1032737848473532159789552
| null | null | null |
[
"sys.009_set.000_184"
] |
[
"DS_qgi1kbtdzwmm_0"
] | 2023-12-02T02:53:07 |
1002642141242492739804527050190874638039406385031757110130193093017375043778867841968948288912898737538409420632284293912240450840557125786836601381391980
|
CO_1002642141242492739804527
|
HfO2_DPGEN_PRB_2021
|
[
"Jing Wu",
"Yuzhi Zhang",
"Linfeng Zhang",
"Shi Liu"
] |
Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
[
[
1,
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1
]
] |
[
3
] |
2023
|
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LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
|
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|
DS_qgi1kbtdzwmm_0
|
HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
|
Hf32O64
|
HfO2
|
A2B
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
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MD_6206330277285791203846415
| 2024-08-16T14:33:44 |
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PO_8584256678141332737179771
| null | null | null |
[
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[
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] | 2023-12-02T02:53:07 |
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CO_1002862201359779462125382
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HfO2_DPGEN_PRB_2021
|
[
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Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
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3
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2023
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
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DS_qgi1kbtdzwmm_0
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HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
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Hf32O64
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HfO2
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
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MD_6206330277285791203846415
| 2024-08-16T14:12:06 |
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PO_1464543695819926618863838
| null | null | null |
[
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[
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] | 2023-12-02T02:53:08 |
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CO_1003159808271572236425238
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HfO2_DPGEN_PRB_2021
|
[
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Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
[
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3
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2023
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LGPL-3.0-only
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{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
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|
DS_qgi1kbtdzwmm_0
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HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
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Hf32O64
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HfO2
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VASP
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DFT-PBE
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{"input": {"encut": {"value": 600, "units": "eV"}}, "k-point": "2 x 2 x 2", "hash": "6206330277285791203846415246770068132175496270059051527097048057674614626525613994954917999219692300919839515752547920892815412826688814749661303848466281", "id": "MD_6206330277285791203846415"}
|
MD_6206330277285791203846415
| 2024-08-16T14:11:51 |
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|
PO_4875075969634921030613617
| null | null | null |
[
"sys.001_set.000_1780"
] |
[
"DS_qgi1kbtdzwmm_0"
] | 2023-12-02T02:53:05 |
10031665179525763222513826873575681223026889742607767695298046658667829521988595544463193882017908147581662668964391742878582855375908861743204456792578286
|
CO_1003166517952576322251382
|
HfO2_DPGEN_PRB_2021
|
[
"Jing Wu",
"Yuzhi Zhang",
"Linfeng Zhang",
"Shi Liu"
] |
Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
|
[
"Hf",
"O"
] | 2 | 28,562 | 28,564 | 2,741,376 | 0 | 28,562 | 0 | 28,562 | 0 | 28,562 | -933.968798 | 219.985865 | 0 | 2023-12-01T21:57:45 |
[
[
1,
1,
1
]
] |
[
3
] |
2023
|
[
0.3333333333333333,
0.6666666666666666
] |
LGPL-3.0-only
|
{'source-publication': 'https://doi.org/10.1103/PhysRevB.103.024108', 'source-data': 'https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen', 'other': None}
|
10.60732/9fbd0fcb
|
7799736414165241621625261964783760186188150246579514782859771629890475850106172573001873696218774241421388409588991957526755072560548966338654103573772036
|
DS_qgi1kbtdzwmm_0
|
HfO2_DPGEN_PRB_2021__Wu-Zhang-Zhang-Liu__DS_qgi1kbtdzwmm_0
|
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in Data Studio
Dataset
HfO2 DPGEN PRB 2021
Description
Approximately 28,500 configurations of hafnia (HfO2) used in the training of a DP model for the prediction of properties of various hafnia polymorphs, including transition barriers between different phases.
Additional details stored in dataset columns prepended with "dataset_".
Dataset authors
Jing Wu, Yuzhi Zhang, Linfeng Zhang, Shi Liu
Publication
https://doi.org/10.1103/PhysRevB.103.024108
Original data link
https://www.aissquare.com/datasets/detail?pageType=datasets&name=HfO2-dpgen
License
Lgpl-3.0
Number of unique molecular configurations
28564
Number of atoms
2741376
Elements included
Hf, O
Properties included
energy, atomic forces, cauchy stress
Cite this dataset
Wu, J., Zhang, Y., Zhang, L., and Liu, S. HfO2 DPGEN PRB 2021. ColabFit, 2023. https://doi.org/10.60732/9fbd0fcb
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