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

Understanding the application of covalent adaptable networks in self-repair materials based on molecular simulation

Covalent adaptable networks (CANs) are widely used in the field of self-repair materials. They are a group of covalently cross-linked associative polymers that undergo reversible chemical reactions, and can be further divided into dissociative CANs (Diss-CANs) and associative CANs (Asso-CANs). Self-repair refers to the ability of a material to repair itself without external intervention, and can be classified into self-adhesion and self-healing according to the utilization of open stickers. Unlike conventional materials, the viscoelastic properties of CANs are influenced by both the molecular structure and reaction kinetics, ultimately affecting their repair performance. To gain deeper insight into the repair mechanism of CANs, we conducted simulations by using the hybrid MC/MD algorithm, as previously proposed in our research. Interestingly, we observed a significant correlation between reaction kinetics and repair behavior. Asso-CANs exhibited strong mechanical strength and high creep resistance, rendering them suitable as self-adhesion materials. On the other hand, Diss-CANs formed open stickers that facilitated local relaxation, aligning perfectly with self-healing processes. Moreover, the introduction of crosslinkers in the form of small molecules enhanced the repair efficiency. Theoretically, it was found that the repair timescale of Asso-CANs is slower than that of Diss-CANs with identical molecular structures. Our study not only clarifies the similarities and differences between Diss-CANs and Asso-CANs in terms of their self-repairing capabilities, but more importantly, it provides valuable insights guiding the effective utilization of CANs in the development of self-repair materials.

Structural and dynamic heterogeneity in associative networks formed by artificially engineered protein polymers

This work investigates static gel structure and cooperative multi-chain motion in associative networks using a well-defined model system composed of artificial coiled-coil proteins. The combination of small-angle and ultra-small-angle neutron scattering provides evidence for three static length scales irrespective of protein gel design which are attributed to correlations arising from the blob length, inter-junction spacing, and multi-chain density fluctuations. Self-diffusion measurements using forced Rayleigh scattering demonstrate an apparent superdiffusive regime in all gels studied, reflecting a transition between distinct "slow" and "fast" diffusive species. The interconversion between the two diffusive modes occurs on a length scale on the order of the largest correlation length observed by neutron scattering, suggesting a possible caging effect. Comparison of the self-diffusive behavior with characteristic molecular length scales and the single-sticker dissociation time inferred from tracer diffusion measurements supports the primarily single-chain mechanisms of self-diffusion as previously conceptualized. The step size of the slow mode is comparable to the root-mean-square length of the midblock strands, consistent with a single-chain walking mode rather than collective motion of multi-chain aggregates. The transition to the fast mode occurs on a timescale 10-1000 times the single-sticker dissociation time, which is consistent with the onset of single-molecule hopping. Finally, the terminal diffusivity depends exponentially on the number of stickers per chain, further suggesting that long-range diffusion occurs by molecular hopping rather than sticky Rouse motion of larger assemblies. Collectively, the results suggest that diffusion of multi-chain clusters is dominated by the single-chain pictures proposed in previous coarse-grained modeling.