‘Unsticking’ and exposing the surface area of graphene bilayers via randomly distributed nanoparticles

The exemplary properties of graphene and the potential inclusion of nanoparticles have suggested applications in energy storage, catalysts and sensing. A critical feature of the performance of these nanocomposites is the distribution of nanoparticles and the exposed area of the graphene. Here we report a computational analysis exploring the effect of the dispersion of nanoparticles between layers of graphene, characterizing both solvent accessible surface area (SASA) and inter-graphene adhesion energy (ΔEg). We find a maximum number of nanoparticles before the accessible graphene surface area decreases, and a limit where the system separates as the graphene layers no longer ‘stick’.