CGM-MLP -- ColabFit
Collection
Datasets from CGM-MLP in ColabFit format • 14 items • Updated
property_id string | property_hash string | last_modified timestamp[us] | dataset_id string | multiplicity int32 | software string | method string | energy float64 | atomic_forces list | cauchy_stress list | cauchy_stress_volume_normalized bool | electronic_band_gap float64 | electronic_band_gap_type string | formation_energy float64 | adsorption_energy float64 | atomization_energy float64 | max_force_norm float64 | mean_force_norm float64 | energy_above_hull float64 | configuration_id string | configuration_hash string | structure_hash string | cell list | positions list | pbc list | chemical_formula_hill string | chemical_formula_reduced string | chemical_formula_anonymous string | elements list | elements_ratios list | atomic_numbers list | nsites int32 | nelements int32 | nperiodic_dimensions int32 | dimension_types list | names list | labels list | property_metadata_path string | configuration_metadata_path string | hash string | configuration_metadata string | property_metadata string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PO_4922507345081081357817802 | 4922507345081081357817802827749614907423137402369708165792676566427191451616806707355565480904814940195086145811197059192411695626028003573957195486771514 | 2025-04-16T15:41:03 | DS_j6w4ru800ukq_0 | 1 | CP2K | DFT-PBE+D3 | -1,322.532313 | [
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PO_4921852914120315785447673 | 4921852914120315785447673878984425509669899715017311099400030518261150993617277986759368916357016499062912378023393009342689129303875438275520556860084605 | 2025-04-16T15:43:58 | DS_j6w4ru800ukq_0 | 1 | CP2K | DFT-PBE+D3 | -1,031.036849 | [
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] | true | null | null | null | null | null | 2.98844 | 1.132782 | null | CO_4796883987968543096902377 | 4796883987968543096902377398859701468570805555405710208458734001194370757998248760937798965102884054170382847750551899706335771726220441278442879422998694 | 7613626565064114596795256963148108317978577330303953250625453746479611103004851423854723100325263367462893798208939841979746080398121978818803505893687791 | [
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... | 291 | 2 | 3 | [
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PO_4902914541373243534111581 | 4902914541373243534111581441303476817620872089106639037968792606693128300288639353046634244068785629465925982859837222553927881729146762252026213181592553 | 2025-04-16T17:03:28 | DS_j6w4ru800ukq_0 | 1 | CP2K | DFT-PBE+D3 | -1,295.727457 | [
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] | true | null | null | null | null | null | 63.887565 | 2.076366 | null | CO_4219746398960635221348365 | 4219746398960635221348365026637781493052959787574580502750014412756273797492864547696946536575199978262163870265914710868115863869311422676066764793442183 | 712099700376813628677299720065289184123571140079470716063803852616264890473490198267930157153446985219148618932258700529609651880325259377292138210687378 | [
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... | 329 | 2 | 3 | [
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PO_4902308146524986898247620 | 4902308146524986898247620271633000289482991233460745503070410703112479670075321569818922414580433936953567622912475212720580044211410189595981594417868979 | 2025-04-16T18:18:40 | DS_j6w4ru800ukq_0 | 1 | CP2K | DFT-PBE+D3 | -1,317.131951 | [
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PO_4948244213550801405748786 | 4948244213550801405748786761578694501524204519070288641030479507463911486095605714469892211807181369679197030506676302690083307147982586451810078448098329 | 2025-04-16T20:58:52 | DS_j6w4ru800ukq_0 | 1 | CP2K | DFT-PBE+D3 | -1,261.151959 | [
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PO_4964494454593889544514670 | 4964494454593889544514670395518329131919497160118226566429094901435105185996952689668184237991838706403482142727081108711798280631805620391379917378752165 | 2025-04-16T17:54:01 | DS_j6w4ru800ukq_0 | 1 | CP2K | DFT-PBE+D3 | -1,023.418901 | [
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End of preview. Expand in Data Studio
Cite this dataset
Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. CGM-MLP natcomm2023 screening deposited-carbon@Cu train. ColabFit, 2024. https://doi.org/10.60732/535052eb
Cite this dataset
Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. CGM-MLP natcomm2023 screening deposited-carbon@Cu train. ColabFit, 2024. https://doi.org/10.60732/535052ebThis dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_j6w4ru800ukq_0
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Dataset Name
CGM-MLP natcomm2023 screening deposited-carbon@Cu train
Description
1090 structures uniformly selected from the MD/tfMC simulation during the training process of CGM-MLPs. 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.
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
1091
Number of atoms
362898
Elements included
C, Cu
Properties included
energy, atomic forces, cauchy stress
Usage
ds.parquet: Aggregated dataset information.co/directory: Configuration rows each include a structure, calculated properties, and metadata.cs/directory : Configuration sets are subsets of configurations grouped by some common characteristic. Ifcs/does not exist, no configurations sets have been defined for this dataset.cs_co_map/directory : The mapping of configurations to configuration sets (if defined).
ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:
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