This study aims to clarify the relationship and establish a theoretical framework of covalent adaptive networks (CANs), which enable thermosetting epoxies to have excellent self-healing properties, facilitating their recyclability.
A scaling model was developed to describe CANs’ viscoelastic behavior in thermosetting epoxies. A relaxation time function was built to characterize CAN chemical kinetics (linked to network reorganization-induced topological and viscoelastic transitions), an extended Maxwell model derived the self-healed CAN’s stress–strain relationship, and model predictions were validated with experimental data.
The scaling model was successfully established and verified; it clarified how molecular chemical kinetics regulate CANs’ self-healing performance. The model’s applicability under complex conditions (e.g. extreme temperature, humidity) and to different types of thermosetting epoxies/CANs requires further exploration.
This paper provides a fundamental framework for optimizing CANs’ molecular structure and viscoelastic properties, thereby enhancing thermosetting epoxies’ self-healing efficiency and recyclability and promotes the development of recyclable polymer materials, aligning with green development and circular economy concepts, and reducing environmental pressure from polymer waste, which fills the research gap in relevant scaling models, offering new theoretical support for designing self-healing thermosetting epoxies.
