Dynamically cross-linked polymer networks have promising potential to serve as self-healing materials, but this is often limited to occur at elevated temperature. We overcome this limitation by refinement of an earlier approach to synthesize dynamically cross-linked polydimethyl­siloxane networks such to show stress relaxation and self-healing at room temperature on short time scales, which we probe by oscillatory shear rheology and piercing experiments. Our studies reveal a direct correlation between the amount of anionic groups in the polymer networks and their stress-relaxation and self-healing rates, allowing these materials to be designed in a rational fashion.

Hydrogels based on poly(N-isopropylacrylamide) (pNIPAAm) exhibit a thermo-reversible volume phase transition from swollen to deswollen states. This change of the hydrogel volume is accompanied by changes of the hydrogel elastic and Young's moduli and of the hydrogel interfacial interactions. To decouple these parameters from one another, we present a class of submillimeter sized hydrogel particles that consist of a thermosensitive pNIPAAm core wrapped by a nonthermosensitive polyacrylamide (pAAm) shell, each templated by droplet-based microfluidics. When the microgel core deswells upon increase of the temperature to above 34 °C, the shell is stretched and dragged to follow this deswelling into the microgel interior, resulting in an increase of the microgel surficial Young's modulus. However, as the surface interactions of the pAAm shell are independent of temperature at around 34 °C, they do not considerably change during the pNIPAAm-core volume phase transition. This feature makes these core-shell microgels a promising platform to be used as building blocks to assemble soft materials with rationally and independently tunable mechanics.

The chain dynamics in supramolecular polymer networks is determined by the interplay of the kinetics of transient interchain association and relaxation of the network chains themselves. This interplay can be addressed by studying model supramolecular polymer networks in which the number of associative side groups and the molar mass of the covalently jointed backbone polymers are both varied systematically. To realize this idea, we use precursor chains with three different molar masses, which comes along with different extents of entanglement in the melt state. For each molar mass, the precursor polymers are functionalized with three different relative contents of associative side groups, giving rise to transient network formation in the melt state. We evaluate the chain dynamics in these transient networks by probing the diffusivity of fluorescently labeled tracer chains by fluorescence recovery after photobleaching (FRAP). In these studies, we find that the presence of entanglements markedly outweighs the influence of transient associative interactions.

Thermoresponsive polymer gels exhibit pronounced swelling and deswelling upon changes in temperature, making them attractive for applications in sensing and actuation. This volume phase transition can be discussed in terms of mean‐field theoretical pictures to assess at which conditions it occurs continuously or discontinuously. However, this treatment disregards static nano‐ and micrometer‐scale inhomogeneities in gel polymer networks, which are a common feature of these materials. To check for the impact of such structural complexity, droplet‐based microfluidics are used to fabricate sub‐millimeter‐sized gel particles that exhibit critical compositions at the border between continuous to discontinuous volume phase transitions, along with determined static spatial polymer‐network heterogeneity on the nano­meter and micrometer length scales, which is characterized by low‐field NMR. These different microgels are then used to study their swelling and deswelling volume phase transitions from a sub‐millimeter perspective. In this investigation, microgel particles with similar content of crosslinker exhibit similar swelling and deswelling, independent of their extent of static polymer‐network inhomogeneity, in agreement with mean‐field theoretical predictions.