Flexible ionic conductors hold potential for wearable sensors and energy harvesting. However, most gel-based conductors suffer from solvent evaporation and liquid leakage, limiting practical applications. Although solid-state ionic conductors mitigate these issues, achieving strong mechanics, high conductivity, self-healing, and stability remains challenging. Here, by integrating supramolecular engineering and dynamic covalent adaptive networks, a self-healing polyurethane-based solid-state ion-conductive elastomer (DACPU/100Li) with outstanding overall properties is successfully synthesized. DACPU/100Li exhibits ultrahigh ionic conductivity (1.23 × 10- 3 S cm-1) and high tensile strength (7.62 MPa), along with an elongation at break of 1200%. Additionally, it exhibits excellent tear resistance and a fracture energy of 45.6 kJ m- 2, along with 96% self-healing efficiency (after self-healing at 120 °C for 24 h), good recyclability, and stability under extreme conditions. The DACPU/100Li-based sensor has high sensitivity (5.89) and a wide strain range (0.1-1000%). Integrated with machine learning, it enables precise gesture recognition and human-machine interaction. Furthermore, the triboelectric nanogenerator based on DACPU/100Li achieves a high power density of 3.87 W m- 2. It harvests energy from body motion to power small devices and aids object recognition via machine learning. It is believed that these solid-state ion-conductive elastomers provide new opportunities for wearable electronics, energy harvesting, and ionotronics.
Keywords: conductivity; mechanical strength; multifunctional strain sensors; solid‐state ion‐conductive elastomers; triboelectric nanogenerators.
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