High-Throughput Electrospinning System| Artificial Tactile Perception for Object Recognition and Grabvia Multifunctional lonic Fiber-Based Sensor System

"Jilin University Prof. Peng Sun’s Team: Artificial Tactile Perception for Object Recognition and Grasping via Multifunctional Ionic Fiber Sensor System"

Challenge: Human tactile perception involves skin mechanoreceptors responding to external stimuli and the central nervous system processing this information. However, pressure sensors based on a single sensing mechanism face challenges in simultaneously achieving mechanical stimulus detection and object recognition as bionic tactile skin.

Method: Prof. Peng Sun and Liupeng Zhao’s team at Jilin University proposed a multifunctional ionic fiber membrane modified with 1‐ethyl‐3‐methylimidazolium dicyanamide ([EMIM][DCA]) to achieve high-performance ionic capacitive sensing and triboelectric generation. [EMIM][DCA] was highly doped into thermoplastic polyurethane via unique hydrogen bonds, yielding a capacitive tactile sensor with ultrahigh sensitivity (184.3 kPa⁻¹) and ultralow detection limit (1.9 Pa).

Innovation 1: The dicyanamide ions introduced electron-donating groups into the triboelectric-positive layer, enhancing the triboelectric nanogenerator (TENG) output by 2.47× with excellent stability over 20,000 cycles.

Innovation 2: By integrating these superior tactile and triboelectric properties, a smart glove was developed to capture subtle grasping motions and recognize materials. Expanding the TENG array and incorporating machine learning into an automated sorting gripper further improved object diversity recognition, achieving 99.17% material identification accuracy.