Dual Interactive Mode Human–Machine Interfaces Based on Triboelectric Nanogenerator and IGZO/In2O3 Heterojunction Synaptic Transistor

Author:

Qi Yashuai1,Tang Jing2,Fan Shuangqing1ORCID,An Chunhua3,Wu Enxiu3,liu Jing3

Affiliation:

1. College of Electronics & Information Qingdao University Qingdao 266071 China

2. China National Chemical Communications Construction Group Second Engineering Co., Ltd Qingdao 266555 China

3. State Key Laboratory of Precision Measurement Technology and Instruments School of Precision Instruments and Opto‐electronics Engineering Tianjin University No. 92 Weijin Road Tianjin 300072 China

Abstract

AbstractImitating human neural networks via bio‐inspired electronics advances human‐machine interfaces (HMI), overcoming von Neumann limitations and enabling efficient, low‐energy data processing in the big data era. However, single‐contact mode HMIs have inherent limitations in terms of their capabilities and performances, such as constrained adaptability to dynamic environments, and reduced cognitive processing capabilities. Here, a dual‐interactive‐mode HMI system based on a triboelectric nanogenerator (TENG) and heterojunction synaptic transistor (HJST) is proposed for both contact and non‐contact applications. The TENG incorporates a poly‐methyl meth‐acrylate (PMMA)‐NiCo2S4/S film, in which the NiCo2S4/S composite traps and blocks electrons to optimize charge generation and storage. The heterojunction structure, mitigates the Debye screening effect, thereby improving transistor characteristics and reliability. The integrated TENG‐HJST system exhibits synaptic functions, including excitatory/inhibitory postsynaptic current (EPSC/IPSC), paired‐pulse facilitation/depression (PPF/PPD), and synaptic plasticity, enabling emulation of neural behavior and advanced information processing. Moreover, neural morphology manipulation is demonstrated in practical tasks, such as controlling international chess games. By integrating the TENG‐HJST device with a robotic hand, conscious artificial responses are generated, enhancing event accuracy. This breakthrough in dual‐interactive‐mode interfacing holds promise for HMI systems and neural prostheses.

Funder

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Publisher

Wiley

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