High-Strength, Self-Sensing Multiphase Hydrogels for Load-Bearing Actuation and Logical Human–Machine Interaction

Zhilin Zhang, Jiayi Gu, Lina Wang, Xingchen Cui, Xu Zhai, Yan Xu, He Liu, Deliang Li, Bingle Li, Y Tian, Baoyang Lu, Yu Fu, Tieqiang Wang

Stimuli-responsive shape-changing hydrogels are the most competitive candidates for artificial muscles, electronic skins, and soft robotics. However, existing actuating hydrogels often suffer a trade-off between actuation performance and mechanical strength, which greatly limits their application prospects as actuators under external force loads. Here, we adopt a cascade polymerization strategy to successively introduce electrical sensing and mechanically enhanced polymer network phases into sponge-like PNIPAM hydrogels to achieve PNIPAM-based photothermal-responsive actuating hydrogels with fast response, high strength, and self-sensing performance. The as-prepared hydrogel actuator can execute rapid actuation missions even under external loading far exceeding its own mass and generate differentiated electrical sensing signals according to the magnitude of the external load. Based on the corresponding relationship between the mass of the load and the actuation behavior (such as "0/1" encoding), we develop a novel material-based binary information encoding system. Furthermore, by manufacturing logic gates to analyze differentiated feedback sensing signals and integrating them with Internet of Things technology, a closed-loop logic control system is established for remote logic-based interactive communication. This study fills the gap of traditional hydrogels in load-bearing actuation and complex interactive applications and opens up a new direction for the next generation of smart soft materials.