Metal Oxide Nanowire Synaptic Transistor for Self-Powered Visual Tactile Human–Machine Interaction System

作者：Feiyang Xu, Jiaqi Xu, Xi Zhang, Mengyao Wei, Haining Yu, Jin Chai, Xiaoyang Song, Yuanbin Qin, Fengyun Wang · 发表于：IEEE Transactions on Electron Devices · 年份：2026 · DOI：10.1109/ted.2026.3667497 · 被引用次数：2 · 研究领域：Advanced Memory and Neural Computing、Advanced Sensor and Energy Harvesting Materials、Transition Metal Oxide Nanomaterials

The development of tactile human–machine interaction (T-HMI) technology has received widespread attention due to its potential to enhance the operational realism and expand application scenarios of HMI systems. However, a key challenge remains in converting dynamic tactile signals into intuitive and persistent feedback. To address this, a visual-T-HMI (VT-HMI) system with real-time visual display capability is proposed, which integrates a self-powered triboelectric nanogenerator (TENG) array and InGaZnO nanowire (NW) transistor array for constructing its bionic artificial tactile sensing component, and a visualization module to display the accurate tactile information. In this system, the TENG array responds sensitively to tactile signals, and the synaptic transistor array preprocesses the tactile responses generated by the TENG, enabling neuromorphic preprocessing of the tactile responses, which facilitates the subsequent decoding and leads to a recognition accuracy exceeding 90% for tactile signals. The designed visual-T-HMI system can be utilized to achieve the control of virtual chess movement directions and the reproduction of handwritten letter trajectories, with excellent recognition accuracy (>90%) for tactile signals. This work provides a promising strategy for developing intelligent and multimodal human–machine interaction systems, with potential applications in wearable electronics, remote control, and immersive interactive technologies.