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

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 (CoO_x) 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.