Simulation of small molecule diffusion using continuous space disordered networks

Abstract

Disordered networks were created and kinetic Monte Carlo simulations were conducted in order to assess the effects of jump network connectivity on the diffusion coefficient. Off-lattice jump networks were created using reverse Monte Carlo, with an objective function defined by agreement to specified inter-site connectivity, inter-site (jump path) distance and consecutive jump angle distributions. Both Gaussian and Poisson distributions of connectivity were applied, with average connectivities spanning a range appropriate for small molecules within a variety of polymers. Distance and angle distributions were taken from earlier work on jump networks in polypropylene. At short times, anomalous diffusion with a range of exponents n ≥ 0.4 was found over the domain of average connectivities. At longer times, diffusion was normal for connectivities above the percolation threshold, while particles were trapped for lower connectivities. The percolation threshold was slightly higher for Gaussian distributions of connectivity than for Poisson distributions. The diffusion coefficient increased linearly for connectivities well above the threshold, with slightly faster diffusion occurring for Gaussian distributions of connectivity.