Tough and Healable Shape-Memory Elastomers Enabled by Dynamic Hyperbranched Topological Networks

Integrating rapid self-healability and shape memory into tough polyurethane elastomers is highly desirable for applications of artificial muscles and soft actuators. However, this combination is fundamentally limited by an inherent structural trade-off between strong phase separation and dynamic interactions. Herein, we develop a dynamic hyperbranched topology strategy to engineer gold nanoparticle-crosslinked polyurethane elastomers featuring a hierarchical structure that includes dynamic topological networks, enhanced hard domains with strong hydrogen bonds, and nano-assemblies phase-separated from an amorphous matrix in which soft segments are prepacked for ultrasensitive strain-induced crystallization (SIC). Reversible dissociation/combination of dynamic bonds and progressive rupture of hard domains and assemblies contribute to energy dissipation, while ultrasensitive SIC enables network self-reinforcement, affording a high strength of 53 MPa, a toughness of 483.3 MJ m^-3, and a fracture energy of 352.5 kJ m^-2. Meanwhile, abundant dynamic bonds enable rapid self-healability of the elastomer with a healing efficiency of 93.5% upon 2-min near‑infrared  irradiation. Accompanied by sensitive SIC-induced network fixation, these elastomers show remarkable shape memory with a shape fixation ratio of 91% and a shape recovery ratio of 94.7%. Based on the unprecedented combinational properties, this work establishes a design paradigm for hierarchically structured elastomers that reconcile high mechanical performance with smart stimulus responsiveness.