Ion Gel Pressure Sensor with High Sensitivity and a Wide Linear Range Enabled by Magnetically Induced Gradient Microstructures

In the field of intelligent sensing, a major challenge pertains to the development of capacitive pressure sensors that can precisely detect minute pressure changes and simultaneously exhibit a wide linear range and high sensitivity. This paper develops a novel capacitive pressure sensor inspired by the gradient microstructure of tree frog toe pads, which is suitable for various applications including texture recognition, motion monitoring, and object grasping recognition. The sensor employs magnetic induction technology to precisely control the gradient microstructure morphology and combines it with ionic gel and conductive nanomaterials. These features enable it to not only detect minute pressures as low as 0.5 Pa but also maintain a high sensitivity of 1.51 kPa^-1 and excellent linear response characteristics across a wide pressure range of up to 93.5 kPa. It can accurately capture pulse beats and motion signals, making it suitable for use in human health monitoring. Furthermore, by utilizing the deep learning algorithms, it achieves a 97.39% object recognition accuracy rate in flexible intelligent sorting systems. This work provides a new solution in application fields such as health monitoring and intelligent logistics sorting.