Transistor-like iontronics device based on MXene/Bi 2D heterojunction for human-machine intelligent interaction

Human-machine intelligent interaction (HMII) technology, which is an advanced iteration of human-machine interaction technology, has garnered widespread attention owing to its significant achievements in healthcare and virtual reality research. Nonetheless, these fields often depend on elaborate multi-sensor integrations and face challenges in achieving precise control over robotic manipulation. Herein, a novel transistor-like iontronics pressure sensor based on an MXene/Bi 2D heterojunction is proposed. This transistor-like, flexible, all-solid-state, self-powered iontronics device exhibited a fast response time (66.59 ms), long lifetime (up to 50,000 cycles), and static/dynamic response with linear sensitivity. A deep-learning-assisted single-device HMII system was further constructed. Crucially, the system is adept at monitoring subtle skin deformations triggered by the median and ulnar nerves, efficient real-time decoding of sophisticated hand gestures (recognition accuracy of 95.83%), and precise control of robotic hands using tactile perception feedback. This approach addresses the inherent redundancy in multi-sensor devices used to decode motion across multiple finger joints, marking a significant step forward for iontronics in enhancing the perceptual interaction between humans and machines.