Imitating 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.
Keywords: TENG; dual interactive mode; human–machine interfaces; synaptic transistor.
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