MXene Aerogel Pressure Sensor Improved by Introducing Intermolecular Forces for Human Motion Detection and Voice Recognition

Abstract MXene aerogels, known for their exceptional conductivity, hold significant potential in the development of pressure sensors. However, the van der Waals forces that solely exist between pure MXene nanosheets are inadequate for forming aerogels with high elasticity and mechanical properties, thus restricting the broad application of MXene aerogels in sensor technology. In this research, reduced graphene oxide (RGO) is utilized as the primary framework and incorporate polyaniline (PANI) to enhance intermolecular interaction forces, employing freeze‐drying techniques to fabricate 3D porous‐structured MXene aerogels. This approach significantly enhances the elasticity and electrical responsiveness of the aerogel. The resulting aerogel‐based pressure sensor exhibits high sensitivity (4 kPa −1 ), a wide linear response range (1–20 kPa), rapid response/recovery time (300/100 ms), and excellent stability. The sensor is capable of detecting a variety of pressure signals, from gentle breezes to human motion, and is applied in voice recognition. Using a machine learning framework based on feature engineering, it is possible to accurately identify and classify distinctly pronounced letters from sensor outputs with an accuracy rate as high as 98%. In summary, the high‐performance flexible pressure sensor based on MXene aerogel shows great potential for applications in health monitoring, smart wearable devices, and artificial intelligence.