A dual-mode transparent device for 360° quasi-omnidirectional self-driven photodetection and efficient ultralow-power...

Area of Science:

• Materials Science
• Nanotechnology
• Neuroscience

Background:

• Integrating photodetectors and synaptic devices into a single unit is challenging due to stringent manufacturing requirements.
• Existing devices often lack the multifunctionality needed for advanced neuromorphic applications.

Purpose of the Study:

• To design and demonstrate a monolithic dual-mode transparent device combining self-driven 360° photodetectors and artificial synapses.
• To explore the device's potential for neuromorphic computing and robotic applications.

Main Methods:

• Fabrication of a graphene/(Al,Ga)N nanowire heterojunction.
• Manipulation of carrier transport dynamics via bias voltage control to switch between photodetection and synaptic modes.
• Characterization of optical, electrical, and synaptic properties, including UV/visible rejection ratio, dark current, and energy consumption.

Main Results:

• Successful monolithic integration of quasi-omnidirectional photodetectors and artificial synapses in a transparent device.
• Demonstrated self-driven 360° photodetection at 0 V bias and brain-like synaptic functions (paired-pulse facilitation, plasticity, learning/forgetting) under applied bias.
• Achieved high UV/visible rejection ratio (1.29 × 10⁴), ultra-low dark current (<1 pA), and low energy consumption (2.5 × 10⁻¹⁴ J/event).
• Applied the device for neuromorphic image preprocessing and guiding humanoid robots in motion learning tasks.

Conclusions:

• The designed graphene/(Al,Ga)N nanowire heterojunction enables multifunctional monolithic integration, overcoming previous challenges.
• The device shows significant potential for advanced, low-power neuromorphic computing systems and intelligent robotics.
• This work offers new pathways for manufacturing integrated multifunctional devices.