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Hydrogels containing thermosensitive polymers such as poly(N‐isopropylacrylamide) (P(NIPAm)) may contract during heating and show great promise in fields ranging from soft robotics to thermosensitive biosensors. However, these gels often exhibit low stiffness, tensile strength, and mechanical toughness, limiting their applicability. Through copolymerization of P(NIPAm) with poly(Acrylic acid) (P(AAc)) and introduction of ferric ions (Fe³⁺) that coordinate with functional groups along the P(AAc) chains, here a thermoresponsive hydrogel with enhanced mechanical extensibility, strength, and toughness is introduced. Using both experimentation and constitutive modeling, it is found that increasing the ratio of m(AAc):m(NIPAm) in the prepolymer decreases strength and toughness but improves extensibility. In contrast, increasing Fe³⁺concentration generally improves strength and toughness with little decrease in extensibility. Due to reversible coordination of the Fe³⁺bonds, these gels display excellent recovery of mechanical strength during cyclic loading and self‐healing ability. While thermosensitive contraction imbued by the underlying P(NIPAm) decreases slightly with increased Fe³⁺concentration, the temperature transition range is widened and shifted upward toward that of human body temperature (between 30 and 40 °C), perhaps rendering these gels suitable as in vivo biosensors. Finally, these gels display excellent adsorptive properties with a variety of materials, rendering them possible candidates in adhesive applications.

 

Dynamic networks containing multiple bond types within a continuous network grant engineers another design parameter – relative bond fraction – by which to tune storage and dissipation of mechanical energy. However, the mechanisms governing emergent properties are difficult to deduce experimentally. Therefore, we here employ a network model with prescribed fractions of dynamic and stable bonds to predict relaxation characteristics of hybrid networks. We find that during stress relaxation, predominantly dynamic networks can exhibit long-term moduli through conformationally inhibited relaxation of stable bonds due to exclusion interactions with neighboring chains. Meanwhile, predominantly stable networks exhibit minor relaxation through non-affine reconfiguration of dynamic bonds. Given this, we introduce a single fitting parameter, ξ , to Transient Network Theory via a coupled rule of mixture, that characterizes the extent of stable bond relaxation. Treating ξ as a fitting parameter, the coupled rule of mixture's predicted stress response not only agrees with the network model's, but also unveils likely micromechanical traits of gels hosting multiple bond dissociation timescales.