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Abstract:Graphene is an ideal reinforcement material for metal-matrix composites owing to its exceptional mechanical properties. However, as a 2D layered material, graphene shows highly anisotropic behavior, which greatly affects the mechanical properties of graphene-based composites. In this study, the interaction between an edge dislocation (b = 1/2 (111)) and a pair of graphene nanosheets (GNSs) in GNS reinforced iron matrix composite (GNS/Fe) was investigated using molecular dynamic simulations under simple shearing conditions. We studied the cases wherein the GNS pair was parallel to the (110), (112), and (111) planes, respectively. The results showed that the GNS reinforcement can effectively hinder dislocation motion, which improves the yield strength. The interaction between the edge dislocation and the GNS pair parallel to the (112) plane showed the strongest effect of blocking dislocations among the three cases, resulting in increases in the shear modulus and yield stress of 107% and 1400%, respectively. This remarkable enhancement was attributed to the Orowan "by-passing" strengthening mechanism, whereas cross-slip of dislocation segments was observed during looping around GNSs. Our results might contribute to the development of high-strength iron matrix composites.

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The adhesion feature of graphene on metal substrates is important in graphene synthesis, transfer and applications, as well as for graphene-reinforced metal matrix composites. We investigate the adhesion energy of graphene nanosheets (GNs) on iron substrate using molecular dynamic (MD) simulations. Two Fe–C potentials are examined as Lennard–Jones (LJ) pair potential and embedded-atom method (EAM) potential. For LJ potential, the adhesion energies of monolayer GN are 0.47, 0.62, 0.70 and 0.74 J/m2 on the iron {110}, {111}, {112} and {100} surfaces, respectively, compared to the values of 26.83, 24.87, 25.13 and 25.01 J/m2 from EAM potential. When the number of GN layers increases from one to three, the adhesion energy from EAM potential increases. Such a trend is not captured by LJ potential. The iron {110} surface is the most adhesive surface for monolayer, bilayer and trilayer GNs from EAM potential. The results suggest that the LJ potential describes a weak bond of Fe–C, opposed to a hybrid chemical and strong bond from EAM potential. The average vertical distances between monolayer GN and four iron surfaces are 2.0–2.2 Å from LJ potential and 1.3–1.4 Å from EAM potential. These separations are nearly unchanged with an increasing number of layers. The ABA-stacked GN is likely to form on lower-index {110} and {100} surfaces, while the ABC-stacked GN is preferred on higher-index {111} surface. Our insights of the graphene adhesion mechanics might be beneficial in graphene growing, surface engineering and enhancement of iron using graphene sheets.