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Bioinspired Reconfigurable Vision Sensor Based on InGaN Semiconductor/Hydrogel Heterostructure for Dynamic-Static

Wei Chen1, Daohao Wang1, Xin Liu1

  • 1iGaN Laboratory, School of Microelectronics, University of Science and Technology of China, Hefei, 230000, P. R. China.

Advanced Materials (Deerfield Beach, Fla.)
|November 13, 2025
PubMed
Summary
This summary is machine-generated.

Researchers developed a novel bio-inspired vision sensor using InGaN nanowires and hydrogel. This dual-function device captures both static images and dynamic motion, advancing artificial vision systems.

Keywords:
III‐nitride nanowiresdual‐function vision sensordynamic‐static visionphotodetectionphotosynapse

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Area of Science:

  • Optoelectronics
  • Materials Science
  • Artificial Intelligence

Background:

  • Intelligent optoelectronic devices are key for advanced machine vision.
  • Current systems often struggle to simultaneously capture dynamic motion and static images efficiently.

Purpose of the Study:

  • To propose a bio-inspired reconfigurable vision sensor architecture.
  • To enable dual-mode operation for photodetection and photosynaptic capabilities.
  • To enhance dual-mode optoelectronic performance through material engineering.

Main Methods:

  • Fabrication of an Indium Gallium Nitride (InGaN) nanowire/hydrogel heterojunction.
  • Electrical modulation of electron transport dynamics at the heterointerface.
  • Decoration with Cobalt Oxide (CoOx) nanoparticles to improve charge transport.

Main Results:

  • The sensor demonstrated high responsivity and microsecond response speed in photodetection mode for static image sensing.
  • In photosynaptic mode, it exhibited synaptic behavior for temporal-dependent image memory and motion perception.
  • A binocular artificial vision system successfully recognized motion trajectories and object positions, showcasing dynamic-static fusion.

Conclusions:

  • The proposed architecture offers a promising pathway for high-performance, self-powered, dual-function vision sensors.
  • This technology advances the development of next-generation, energy-efficient artificial vision systems.
  • The bio-inspired design enhances capabilities for complex machine vision tasks.