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<p>Neuromorphic visual systems have attracted tremendous attention for their in-sensor image sensing and information preprocessing paradigm that replicates human visual system. However, current neuromorphic visual devices employed in these systems still confront challenges on lateral conductivity, air-stability, and photo-response linearity. Here, we demonstrate a neuromorphic image-sensing transistor array based on a tri-layer van der Waals heterostructure composed of MoS<sub>2</sub>, (BA)<sub>2</sub>PbI<sub>4</sub> and graphdiyne (GDY). The top MoS<sub>2</sub> layer with high intrinsic mobility serves as carrier-transport channel, while encapsulating the 2D perovskite to shield it from ambient air. The sandwiched 2D-(BA)<sub>2</sub>PbI<sub>4</sub> nanosheet converts light into electricity, and functions as a photo-tunable tunneling junction, facilitating unidirectional tunneling of photo-generated carriers toward the underlying GDY layer. GDY, featuring well-distributed alkyne bonds, enables uniform interaction and storage of charges. The device demonstrates long-term air-stability (&gt;10 weeks), highly competitive linearity in synaptic transistor weight modulation (<i>α</i><sub>P</sub> = 0.006, <i>α</i><sub>D</sub> = 0.025), and remarkably low energy consumption (~41.8 aJ per synaptic event) among 2D heterojunction synaptic transistors. Furthermore, a hardware-level neuromorphic kernel constructed using a synaptic array of these heterostructure devices realizes spatiotemporal neuromorphic in-sensor dynamic image processing and trajectory detection for object movement. This work provides hardware architecture for the next-generation neuromorphic vision.</p>

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High-linearity all-2D heterojunction-based neuromorphic image-sensing transistor array with a sandwiched tunneling layer for dynamic vision

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月22日

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  • Yiming Yuan,
  • Yinxing Zhang,
  • Jie Wang,
  • Tianci Wang,
  • Ruotao Yu,
  • Zhipeng Xu,
  • Jialiang Xu,
  • Wentao Xu

摘要

Neuromorphic visual systems have attracted tremendous attention for their in-sensor image sensing and information preprocessing paradigm that replicates human visual system. However, current neuromorphic visual devices employed in these systems still confront challenges on lateral conductivity, air-stability, and photo-response linearity. Here, we demonstrate a neuromorphic image-sensing transistor array based on a tri-layer van der Waals heterostructure composed of MoS2, (BA)2PbI4 and graphdiyne (GDY). The top MoS2 layer with high intrinsic mobility serves as carrier-transport channel, while encapsulating the 2D perovskite to shield it from ambient air. The sandwiched 2D-(BA)2PbI4 nanosheet converts light into electricity, and functions as a photo-tunable tunneling junction, facilitating unidirectional tunneling of photo-generated carriers toward the underlying GDY layer. GDY, featuring well-distributed alkyne bonds, enables uniform interaction and storage of charges. The device demonstrates long-term air-stability (>10 weeks), highly competitive linearity in synaptic transistor weight modulation (αP = 0.006, αD = 0.025), and remarkably low energy consumption (~41.8 aJ per synaptic event) among 2D heterojunction synaptic transistors. Furthermore, a hardware-level neuromorphic kernel constructed using a synaptic array of these heterostructure devices realizes spatiotemporal neuromorphic in-sensor dynamic image processing and trajectory detection for object movement. This work provides hardware architecture for the next-generation neuromorphic vision.