A tutorial review of linear rheology for polymer chemists: basics and best practices for covalent adaptable networks

Abstract

Covalent adaptable networks (CANs) are an emerging class of soft materials that combine the contradictory traits of thermosets and thermoplastics. They possess dynamic covalent cross-links between chains that exchange through a chemical reaction. Because the flow behavior of CANs reflects the interplay between the cross-link exchange kinetics and polymer backbone dynamics, careful rheological characterization is necessary to illuminate how chemical structure governs viscoelasticity. Yet, rheology presents a significant challenge for polymer chemists as an analytical technique because of the complexity of the measurement and data analysis. Considering the prevalence and significance of rheology in the field of soft matter, however, it is essential for modern polymer chemists to possess a foundation in conducting and interpreting viscoelastic experiments. This tutorial review is an introduction to linear rheology, which focuses on measurements using small strain conditions. It begins by providing a comprehensive discussion of stress relaxation, creep and recovery, and small-amplitude oscillatory shear experiments, highlighting their respective advantages and disadvantages. It explains the concepts of relaxation spectra and time–temperature superposition using simple mathematical arguments and graphical analysis. The review delves into the intricacies of polymer structure–viscoelasticity relationships, focusing on classical thermosets and thermoplastics. It also identifies common sources of experimental artifacts that affect rheology experiments. Towards the end, best practices for performing rheology on CANs are demonstrated using examples from the literature. To further enhance understanding, the review illustrates quantitative rheological models using experimental data from a commercial polymer. Supplementary spreadsheets enable readers to practice time–temperature superposition and relaxation spectrum analysis techniques.