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Intelligent Tribotronic Transistors Toward Tactile Near‐Sensor Computing
Author(s) -
Lei Hao,
Yin ZiYi,
Huang Peihao,
Gao Xu,
Zhao Chun,
Wen Zhen,
Sun Xuhui,
Wang SuiDong
Publication year - 2025
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.202401913
Subject(s) - materials science , tactile sensor , transistor , triboelectric effect , sensitivity (control systems) , pressure sensor , nanotechnology , computer science , optoelectronics , artificial intelligence , electrical engineering , electronic engineering , robot , voltage , mechanical engineering , composite material , engineering
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.