The use of rheology and terminal flow relaxation times to predict healing behavior at long healing times is by now quite well accepted. In this work we go one step further and explore the use of macro-rheology (in particular the stored work of deformation) to predict the early stage interfacial healing properties (fracture resistance) of a set of self-healing polyurethanes. The interfacial healing is measured by single edge notch fracture experiments, using short healing times and a low healing temperature to exclude the effect of long range molecular motion on mechanical properties restoration. The systems based on aromatic diisocyanates show high fracture resistance after healing, while very limited restoration of the mechanical properties is observed for aliphatic and cycloaliphatic based polyurethanes. Linear sweep rheology and time-temperature-superposition allow obtaining the macro-rheological master curve and the mechanical relaxation spectra (H(t)). The application of a recently established deconvolution protocol to the H(t) gives the characteristic relaxation times and stored works of deformation associated to individual dynamic processes such as segmental motion, reversible bonds, and terminal flow. It is found that the calculated stored works of deformation related to the reversible bond relaxation reproduce the trend observed by fracture resistance at healed interfaces and reveal a qualitative correspondence between reversible bonds work of deformation and interfacial healing fracture resistance. Moreover, the method seems to point to the existence of a threshold interfacial work of deformation below which no efficient load transfer can be observed.

Shape memory polymers (SMPs) are dynamic materials able to recover previously defined shapes when activated by external stimuli. The most common stimulus is thermal energy applied near thermal transitions in polymers, such as glass transition (T_g) and melting (T_m) temperatures. The magnitude of the geometrical changes as well as the amount of force and energy that a SMP can output are critical properties for many applications. While typically deformation steps in the shape memory cycles (SMC) are performed at temperatures well above thermal transitions used to activate shape changes, significantly greater amounts of strain, stress, and mechanical energy can be stored in T_g-based SMPs when deformed near their T_g. Since maximum shape memory storage capacity can be appraised by evaluating the viscoelastic length transitions (VLTs) in a single dynamic mechanical analysis (DMA) experiment, this study correlates VLTs with the measured storage capacities obtained from stress-strain experiments for a broad range of well-defined crosslinked acrylates, epoxies, and polyurethanes. This systematic approach allows for assessment of crosslink/junction density (ν_j), viscoelasticity, and chemical composition effects on maximum deformability, and enables predictions of the magnitude of shape memory properties across a wide variety of polymers. These studies demonstrate that the maximum storable strain (ε-store_max) can be accurately predicted using junction density (ν_j) and shape memory factor (SMF), the latter accounting for the contribution of chemical makeup.