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Motivated by the substantial interest in various fillers to enhance the barrier properties of polymeric films, especially graphene derivatives, we perform a computational screening of obstructed diffusion to explore the design parameter space of nanoplatelet-filled composites synthesized in silico. As a model for the nanoplatelets, we use circular and elliptical nonoverlapping and impermeable flat disks, and diffusion is stochastically simulated using a random-walk model, from which the effective diffusivity is calculated. On the basis of 4000 generated structures and diffusion simulations, we systematically investigate the impact of different nanoplatelet characteristics such as orientation, layering, size, polydispersity, shape, and amount. We conclude that the orientation, size, and amount of nanoplatelets are the most important parameters and show that using nanoplatelets oriented perpendicular to the diffusion direction, under reasonable assumptions, with approximately 0.2% (w/w) graphene, we can reach 90% reduction and, with approximately 1% (w/w) graphene, we can reach 99% reduction in diffusivity, purely because of geometrical effects, in a defect-free matrix with perfect compatibility. Additionally, our results suggest that the existing analytical models have some difficulty with extremely large aspect ratio (extremely flat) nanoplatelets, which calls for further development.

Computational Screening of Diffusive Transport in Nanoplatelet-Filled Composites: Use of Graphene To Enhance Polymer Barrier Properties