Avian Bone‐Inspired Super Fatigue Resistant MXene‐Based Aerogels with Human‐Like Tactile Perception for Multilevel Information Encryption Assisted by Machine Learning

Abstract Developing multimodal sensors with human‐like tactile perception is highly desirable for wearable devices, electronic skins (e‐skins), and human‐machine interfaces. However, realizing decoupled signal output and high‐precision measurement remains challenging. Superelastic conductive aerogels are ideal materials for fabricating multimodal sensors as they can convert pressure and temperature stimuli into different electrical signals. Herein, inspired by the microstructure of lightweight and robust avian bones, a biomimetic lamellar silica nanofiber/MXene aerogel (LSMA) sensor for decoupled pressure and temperature sensing is first developed. The avian bone‐like lamellae‐strut structure endows the ultralight LSMA with superb fatigue resistance of 99.1% height retention after 10 000 compression cycles, which is second to none in the reported MXene‐based aerogels. Meanwhile, benefiting from the advantages of the aerogel structure, the LSMA sensor integrating piezoresistive and thermoelectric effects has an ultrahigh temperature resolution of 0.07 K and the lowest pressure detection limit of 0.20 Pa in the reported pressure‐temperature sensors. The unique performance renders it a promising platform for wearable physiological monitoring and tactile e‐skin. Furthermore, an innovative multilevel encryption protection system assisted by machine learning is designed based on the LSMA sensing array as the interactive terminal. This study provides novel insights into the design and application of multimodal sensors.