Tetrachromatic vision-inspired neuromorphic sensors with ultraweak ultraviolet detection

Area of Science:

• Materials Science
• Optoelectronics
• Artificial Intelligence

Background:

• Detecting invisible ultraviolet (UV) light is crucial for advanced artificial vision systems but challenging due to environmental variability.
• Existing UV detection methods often lack sensitivity, memory, and processing capabilities required for complex visual perception.

Purpose of the Study:

• To develop a controllable, UV-ultrasensitive neuromorphic vision sensor (NeuVS) inspired by natural visual systems.
• To integrate sensing, memory, and processing functions into a single device for enhanced UV perception.

Main Methods:

• Utilized organic phototransistors (OPTs) as the core component for sensing, memory, and processing.
• Engineered the active layer with an asymmetric molecular structure for enhanced UV absorption and sensitivity.
• Constructed an artificial neural network using the NeuVS array's wavelength-selective response and multi-level optical memory.

Main Results:

• The fabricated NeuVS demonstrated ultrasensitive detection of 370 nm UV light at intensities as low as 31 nW cm⁻², achieving high optical figures of merit.
• The NeuVS array exhibited robust image sensing and memorization capabilities.
• UV image recognition accuracy was significantly improved from 46% to 90% by filtering visible light noise.

Conclusions:

• The developed UV-ultrasensitive NeuVS offers a promising solution for advanced artificial visual perception systems requiring sensitive UV detection.
• The integration of sensing, memory, and processing in the NeuVS enables efficient extraction and identification of invisible UV information.
• This technology has the potential to significantly enhance the performance of artificial vision systems in complex environments.