Effect of chain architecture on self-diffusion in a model associative network.

Associative networks are ubiquitous both in natural and synthetic materials, and self-diffusion within these networks dictates many of their desirable properties such as self-healing and stress relaxation. Self-diffusion studies of various associative networks have shown that over length scales of several times the radius of gyration, the dynamics of the network lead to the observation of an apparent super-diffusive regime prior to transitioning to the Fickian regime at larger length scales. In this work, the effect of chain architecture was investigated by comparing the self-diffusion of a random copolymer with one where the stickers are clustered at the end of the chain. Since the chemical composition of the model associative networks is kept constant, this approach allows for a more direct comparison of the role of chain architecture. The insights gained from this study will improve our understanding of the effect of sticker distribution on the transport properties of natural and synthetic associative networks and how it could impact the macroscopic properties that rely on these processes.