(112c) A Faster Simulation Method for Diffusion in Confinement

In this talk I will describe our investigation of self-and collective-diffusion behavior of gases adsorbed in micro-porous materials, with the aim of developing faster techniques to simulate diffusion using concepts from statistical mechanics. The self-diffusion behavior of adsorbed gases has previously been calculated without the use of (often time-consuming) molecular dynamics simulations, but instead from an adaptation of Transition State theory, considering adsorbate movement as a series of uncorrelated hops. In this work we further develop these methods to enable the efficient calculation of the collective-diffusion coefficient with a kinetic Monte Carlo simulation. This investigation has three notable results. 1) A new mixing rule was derived for the transmission coefficient between two cages of unequal loading, and validated with explicit simulations. 2) A new approach to the dynamically corrected Transition State theory was developed, allowing for the explicit treatment of fluctuations in cage loading and enabling an adaptation to a kinetic Monte Carlo simulation, which in turn permitted the calculation of the collective diffusion coefficient. 3) These simulations allowed new insights into how the relationship between self- and collective-diffusion behavior is affected by a change in adsorption packing behavior at higher loadings of methane in zeolite LTA, a relationship we further investigated with isobutane in zeolite MFI.