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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2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
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{'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None}
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CGM-MLP_natcomm2023_screening_amorphous_carbon_train
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[
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2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
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{'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None}
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"G_A_P_-_2_0_Training_Dataset_Amorphous_Bulk__Amorphous_Bulk_2390"
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[
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"DS_on6fusdw5n8q_0",
"DS_sz9me9r61581_0",
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CO_1015903951297097399580614
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CGM-MLP_natcomm2023_screening_amorphous_carbon_train
|
[
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
] |
2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
|
[
"C"
] | 1 | 2,558 | 2,559 | 168,191 | 0 | 2,558 | 0 | 2,558 | 0 | 2,558 | -593.645999 | 62,156.822739 | 0 | 2024-01-11T17:52:57 |
[
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2024
|
[
1
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MIT
|
{'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None}
|
10.60732/f340d1d9
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DS_taxwl7jo4f8a_0
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C125
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2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
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2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
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[
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2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
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{'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None}
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[
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2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
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MD_4178802015180711158523341
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[
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CO_1041729693281863209354690
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CGM-MLP_natcomm2023_screening_amorphous_carbon_train
|
[
"Di Zhang",
"Peiyun Yi",
"Xinmin Lai",
"Linfa Peng",
"Hao Li"
] |
2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
|
[
"C"
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MIT
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{'source-publication': 'https://doi.org/10.1038/s41467-023-44525-z', 'source-data': 'https://github.com/sjtudizhang/CGM-MLP', 'other': None}
|
10.60732/f340d1d9
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DS_taxwl7jo4f8a_0
|
CGM-MLP_natcomm2023_screening_amorphous_carbon_train__Zhang-Yi-Lai-Peng-Li__DS_taxwl7jo4f8a_0
|
End of preview. Expand
in Data Studio
Dataset
CGM-MLP natcomm2023 screening amorphous carbon train
Description
2558 structures selected from the GAP-20 database. This dataset was one of the datasets used in testing screening parameters during the process of producing an active learning dataset for Cu-C interactions for the purposes of exploring substrate-catalyzed deposition as a means of controllable synthesis of carbon nanomaterials. The combined dataset includes structures from the Carbon_GAP_20 dataset and additional configurations of carbon clusters on a Cu(111) surface.
Additional details stored in dataset columns prepended with "dataset_".
Dataset authors
Di Zhang, Peiyun Yi, Xinmin Lai, Linfa Peng, Hao Li
Publication
https://doi.org/10.1038/s41467-023-44525-z
Original data link
https://github.com/sjtudizhang/CGM-MLP
License
MIT
Number of unique molecular configurations
2559
Number of atoms
168191
Elements included
C
Properties included
energy, atomic forces, cauchy stress
Cite this dataset
Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. CGM-MLP natcomm2023 screening amorphous carbon train. ColabFit, 2024. https://doi.org/10.60732/f340d1d9
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