Mechanisms of Self-Diffusion of Linear Associative Polymers Studied by Brownian Dynamics Simulation

Anomalous diffusion of associative polymers has been attributed to a coexistence of multiple diffusive modes, though their role in networks with sticker densities below the mean-field limit is unclear. Here, Brownian dynamics simulations are performed to study self-diffusion of linear associative polymers with various sticker densities, revealing a rich interplay between segmental motion, walking diffusion, and hopping diffusion on different length scales. This interplay creates several self-diffusive regimes, including two apparent superdiffusive regimes before terminal Fickian diffusion. The two superdiffusive regimes have distinct origins: while one occurs from a transition from walking to hopping, the second occurs from walking alone due to changes in the chain pervaded volume over time. Each regime is highly sensitive to the sticker density and binding kinetics due to their effects on the walking and hopping modes. Notably, increasing a chain's sticker density promotes loops and enhances the hopping likelihood, resulting in a non-monotonic effect of sticker density on the overall chain diffusivity. Scaling arguments are developed to predict characteristic walking and hopping diffusivities, with good agreement with simulation.