Name: CGM-MLP natcomm2023 screening graphite train
License: MIT

Dataset

CGM-MLP_natcomm2023_screening_graphite_train

Name	CGM-MLP_natcomm2023_screening_graphite_train
Extended ID	CGM-MLP_natcomm2023_screening_graphite_train__Zhang-Yi-Lai-Peng-Li__DS_jasbxoigo7r4_0
Description	40 graphite structures with different lattice constants ranging from 2.0 to 3.2 Å, with a 0.03 Å increment. 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.
Authors	Di Zhang Peiyun Yi Xinmin Lai Linfa Peng Hao Li
DOI	10.60732/85590078 https://commons.datacite.org/doi.org/10.60732/85590078 https://doi.datacite.org/dois/10.60732%2F85590078 https://doi.org/10.60732/85590078 Cite as: Zhang, D., Yi, P., Lai, X., Peng, L., and Li, H. "CGM-MLP natcomm2023 screening graphite train." ColabFit, 2024. https://doi.org/10.60732/85590078. For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types	atomic_forces cauchy_stress energy
Elements	C (100.0%)
Number of Configurations	41
Number of Atoms	1,968
Links	https://github.com/sjtudizhang/CGM-MLP https://doi.org/10.1038/s41467-023-44525-z
Configuration Sets by Name	(None)
Configuration Sets by ID	(None)
Calculated Properties	PO_2074665675484937558212328 PO_3383886034944324413401386 PO_5903441525807785617525229 PO_2107166639277965262501043 PO_3723532845452314420938673 PO_1211624672033680375414844 PO_9266794156478841339807991 PO_6189706894276627703360845 PO_2272905453156085666069247 PO_1291632486350659029602035 PO_5142766741497173660346529 PO_2173327871556024156344237 PO_1987094885924269097416769 PO_1162044279943394615885330 PO_1027165228929365073490726 PO_1181220427618782851308304 PO_1305687808686437361427822 PO_7580003584240978853539695 PO_1073537155164130421524433 PO_2099937011197129792861441 PO_4756139403759181196942193 PO_2835193328188457585772232 PO_5418938030771838579346229 PO_2330326240618695480302059 PO_1308375462133568844321202 PO_5270011353574484541718719 PO_6412390509905794338516322 PO_3407379993646416751708299 PO_8988529835056847519206512 PO_1055007116929149625368385 PO_2647809291320201686727552 PO_4362528900221022455066632 PO_3460670547439646676386671 PO_1263483268720700011263566 PO_4284216006214146565954641 PO_9451872337561104001820050 PO_9162529492863403049616229 PO_4485647682549981067762684 PO_2197485649145371696835062 PO_4369647908946850388667891 PO_3014079916697759717635758
ColabFit ID	DS_jasbxoigo7r4_0
Files	colabfitspec.json

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