Quantitative Prediction of Stress Relaxation Kinetics in Dissociative Covalent Adaptable Networks.

A kinetic-structural model was developed to quantitatively describe the stress relaxation behavior of covalent adaptable networks based on the reversible Diels-Alder chemistry. The model draws on the analogy between stress relaxation and network de-cross-linking, where residual stress is attributed to elastically active network strands. A recursive network analysis, based on the Macosko-Miller approach, is coupled with a model that incorporates the reversible Diels-Alder reaction kinetics, stress-induced bond activation, and the reduced efficiency of bond exchanges during late-stage relaxation. The model was validated using rheological data from two Diels-Alder-based networks, with cross-linking kinetics and equilibrium conversions used to predict initial stresses. The stress relaxation behavior, including characteristic times and shape parameters across varying temperatures and cross-link densities, was accurately predicted using only two temperature-independent parameters. Beyond predictive capabilities, the model enables the extraction of kinetic and thermodynamic parameters from experimental data, supporting its use in both direct simulation and inverse design. Thanks to its low computational cost, the framework facilitates rapid exploration of compositional and structural scenarios, aiding the design of application-specific materials. This approach offers a robust and efficient tool for bridging the gap between dynamic covalent chemistries and the development of functional materials and their advanced processing.