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.