4.8 Article

Significantly improved interfacial shear strength in graphene/copper nanocomposite via wrinkles and functionalization: A molecular dynamics study

Journal

CARBON
Volume 174, Issue -, Pages 335-344

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.carbon.2020.12.026

Keywords

Graphene; Metal matrix composites (MMCs); Interfacial shear strength (IFSS); Wrinkles; Functionalization; Molecular dynamics (MD) simulation

Funding

  1. Australian Research Council [DP160101978]

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Research shows that the use of chemically functionalized graphene fillers can effectively enhance the interaction between graphene and metal matrix, resulting in higher interfacial shear strength. The presence of shear-induced wrinkles and chemical modification can significantly increase graphene's surface roughness, leading to better interfacial interactions between graphene and the metal matrix.
Graphene reinforced metal matrix composites (MMCs) have received extensive research interests as promising structural materials in developing lightweight structures. The mechanical performance of such composites, however, is considerably hindered by weak van der Waal (vdW) interaction between graphene and metal matrix. The present work shows that this challenging issue can be effectively alleviated by the use of chemically functionalized graphene fillers with mechanically induced wrinkles. Our extensive molecular dynamics (MD) simulations on graphene reinforced copper (Cu) composite manifest that the presence of shear-induced wrinkles and chemical modification of graphene using functional groups can significantly increase its surface roughness, enhance the vdW interaction and consequently lead to higher interfacial shear strength (IFSS) between graphene and Cu matrix. Compared with its counterpart functionalized with hydrogen, graphene functionalized with alkyl (methyl, ethyl, propyl, and butyl) offers better interfacial interactions with Cu matrix because these functional groups are longer than hydrogen functional group and can be embedded deeper into the matrix. (C) 2020 Elsevier Ltd. All rights reserved.

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