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

Abstract

ABSTRACT 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.