Alkali Ion-Accelerated Gelation of MXene-Based Conductive Hydrogel for Flexible Sensing and Machine Learning-Assisted Recognition

Conductive hydrogels are promising active materials for wearable flexible electronics, yet it is still challenging to fabricate conductive hydrogels with good environmental stability and electrical properties. In this work, a conductive MXene/LiCl/poly(sulfobetaine methacrylate) hydrogel system was successfully prepared with an impressive conductivity of 12.2 S/m. Interestingly, the synergistic effect of MXene and a lithium bond can significantly accelerate the polymerization process, forming the conductive hydrogel within 1 min. In addition, adding LiCl to the hydrogel not only significantly increases its water retention ability, but also enhances its conductivity, both of which are important for practical applications. The flexible strain sensors based on the as-prepared hydrogel have demonstrated excellent monitoring ability for human joint motion, pulse, and electromyographic signals. More importantly, based on machine learning image recognition technology, the handwritten letter recognition system displayed a high accuracy rate of 93.5%. This work demonstrates the excellent comprehensive performance of MXene-based hydrogels in health monitoring and image recognition and shows potential applications in human-machine interfaces and artificial intelligence.