A computational analysis of graphene adhesion on amorphous silica

We present a computational analysis of the morphology and adhesion energy of graphene on the surface of amorphous silica (a-SiO₂). The a-SiO₂ model surfaces obtained from the continuous random network model-based Metropolis Monte Carlo approach show Gaussian-like height distributions with an average standard deviation of 2.91 ± 0.56 Å, in good agreement with existing experimental measurements (1.68-3.7 Å). Our calculations clearly demonstrate that the optimal adhesion between graphene and a-SiO₂ occurs when the graphene sheet is slightly less corrugated than the underlying a-SiO₂ surface. From morphology analysis based on fast Fourier transform, we find that graphene may not conform well to the relatively small jagged features of the a-SiO₂ surface with wave lengths of smaller than 2 nm, although it generally exhibits high-fidelity conformation to a-SiO₂ topographic features. For 18 independent samples, on average the van der Waals interaction at the graphene/a-SiO ₂ interface is predicted to vary from E_vdW 0.93 eV to 1.56 eV per unit cross-sectional area (nm²) of the a-SiO₂ slab, depending on the choice of 12-6 Lennard-Jones potential parameters, while the predicted strain energy of corrugated graphene on a-SiO₂ is E_st=0.25-0.36 eV/nm². The calculation results yield the graphene/a-SiO₂ adhesion energy of about E_ad 0.7-1.2 eV/nm, given E_ad=E_vdW-E_st. We also discuss how the adhesive strength is affected by the morphological conformity between the graphene sheet and the a-SiO₂ surface.