Highly Stretchable and Conductive MXene-Encapsulated Liquid Metal Hydrogels for Bioinspired Self-Sensing Soft Actuators

Advanced sensation and actuation abilities of various living organisms in nature have inspired researchers to design bioinspired self-sensing soft actuators. However, the majority of conventional soft actuators primarily possess actuation capabilities while lacking a real-time sensing signal feedback. Here, a promising strategy is reported to develop highly stretchable and conductive hydrogels for bioinspired self-sensing soft actuators, which integrate actuation and strain-sensing functions into a single materials system. The conductive hydrogels are designed and fabricated by in situ copolymerization of amino-functionalized MXene-encapsulated liquid metal nanodroplets (LM@A-MXene) and poly(N-isopropylacrylamide) hydrogels with controllable activated nanogels as nano-cross-linkers. The resulting hydrogel presents a compacted conducting network and highly porous microstructure, giving rise to robust integration of high conductivity, excellent strain sensitivity, broad stretchability, high stability, and fast response speed. Interestingly, the gradient network structure, formed by self-precipitation of LM@A-MXene, endows the hydrogel with shape-programmable actuation, light-driven remote control, and self-sensing function. As a proof-of-concept application, the soft gripper based on the self-sensing hydrogel actuators is developed, which can not only grasp, lift, and release objects, but also perceive every movement state by monitoring resistance changes. The proposed self-sensing soft actuator can offer new insights for developing smart soft robotics and other artificial intelligent devices. Endowing the soft materials system with sensing and actuating ability is significant for smart soft robotics. In this work, highly stretchable and conductive MXene-encapsulated liquid metal hydrogels are judiciously designed for developing self-sensing soft actuators that integrate actuation and strain-sensing functions.image