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Scalable Production and Thermoelectrical Modeling of Infusible Functional Graphene/Epoxy Nanomaterials for Engineering Applications

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posted on 2024-07-26, 14:55 authored by Azadeh Mirabedini, Liam Anderson, Dennis Antiohos, Andrew AngAndrew Ang, Mostafa NikzadMostafa Nikzad, Franz Fuss, Nishar Hameed
The growing market for the application of carbon fiber reinforced polymers (CFRP) as structural components has necessitated the need to develop CFRPs with improved matrix properties to avoid the challenges associated with heat dissipation and electric current flow paths within the composites. In this work, we have developed infusible graphene nanoplatelets (GnP)-modified epoxy polymer nanocomposites containing 0.5-5.0 wt % GnP using two different processing techniques, (1) high-shear mechanical mixing (HMM) and (2) ultrasonication. Compared to HMM, ultrasonication enabled the proper exfoliation of graphene sheets within an epoxy matrix without damaging the sheet morphology of the nanoplatelets. The resulting ultrasonicated nanocomposite with the addition of 2 wt % GnP delivers a maximum electrical conductivity of 4.75 × 10-5S/m. Unlike electrical conductivity, thermal conductivity properties of nanocomposites were found to be less dependent on the choice of processing method or restacking of graphene sheets at higher filler loadings. Slight improvements to thermal conductivity values were achieved for samples prepared through HMM compared to the ultrasonication method with a maximum value of 0.45 W m-1K-1at 5 wt % GnP. New effective thermal and electrical conductivity models were defined for randomly oriented two-phase heterogeneous nanocomposites so that the functional characteristics of GnP-epoxy nanocomposites could be predicted at different loadings. Ultimately, the optimized GnP-modified matrix containing 2 wt % GnP was successfully embedded into a carbon fiber laminate composite component using a customized vacuum infusion molding method to enhance the multiscale properties of FRPs. This solvent-free and industrially scalable process may pave the way to a future generation of smart self-sensing reinforced composites.

Funding

Polymers with controllable networks

Australian Research Council

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PDF (Accepted manuscript)

ISSN

0888-5885

Journal title

Industrial & Engineering Chemistry Research

Volume

61

Issue

15

Pagination

16 pp

Publisher

American Chemical Society (ACS)

Copyright statement

Copyright © 2022 American Chemical Society. This is the final peer-reviewed author's accepted manuscript version, hosted under the terms and conditions of the Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license (http://creativecommons.org/licenses/by-nc/4.0/).

Language

eng

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