Intelligent Tribotronic Transistors Toward Tactile Near-Sensor Computing

Abstract

For the next generation of human-machine interaction (HMI) systems, the development of a tactile interaction unit with multimodal, high sensitivity, and real-time perception and recognition is the key. Herein, an artificial tactile near-sensor computing (ATNSC) unit based on a triboelectric tactile sensor and an organic synaptic transistor is reported. By introducing multi-peak microstructures, the mechanical performance of the tactile sensor is optimized, showing a high sensitivity of 0.98 V kPa−1 in the pressure range of 0–10 kPa and maintaining 0.11 V kPa−1 at high pressures up to 350 kPa. Additionally, by designing stripe-like convex structures on the top surface, the sensor is capable of bimodal perception in both pressure and sliding sensations. Furthermore, the organic synaptic transistor, which can be driven by tactile sensing stimuli in a variety of circumstances, is achieved utilizing an ion-rich gelatin dielectric covered by a hydrophobic polymer coating layer. The ATNSC unit well demonstrates the stimuli-dependent short-term memory effect, and it enables tactile near-sensor computing for feature action recognition in an HMI system, laying a solid foundation for the construction of intelligent interaction devices.