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Interface-engineered non-volatile visible-blind photodetector for in-sensor computing.

Ge Li1, Donggang Xie1,2, Qinghua Zhang1

  • 1Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing, China.

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|January 3, 2025
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Summary
This summary is machine-generated.

This study introduces a novel reconfigurable ultraviolet (UV) photodetector with built-in computing. This smart sensor integrates storage and processing, reducing energy use and latency for advanced UV detection applications.

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Area of Science:

  • Materials Science
  • Optoelectronics
  • Artificial Intelligence

Background:

  • Ultraviolet (UV) detection is crucial across many fields, but current systems suffer from high energy consumption and data latency due to separate storage and processing components.
  • Developing integrated solutions for UV detection is essential to overcome these limitations.

Purpose of the Study:

  • To demonstrate a reconfigurable UV photodetector with in-sensor computing capabilities.
  • To enhance non-volatile storage through interface engineering and oxygen reservoirs.
  • To showcase the device's potential for edge detection and pattern recognition in real-world scenarios.

Main Methods:

  • Fabrication of a cerium oxide (CeO2)/strontium titanate (SrTiO3) heterostructure UV photodetector.
  • Interface engineering and introduction of an oxygen reservoir to improve non-volatile storage.
  • Construction of a photodetector array functioning as a single-layer neural network.

Main Results:

  • Achieved significant improvement in non-volatile storage capability of the UV photodetector.
  • Demonstrated in-sensor computing for edge detection and pattern recognition without external units.
  • Successfully simulated and achieved 100% accuracy in locating and classifying corona discharges.

Conclusions:

  • The developed CeO2/SrTiO3 heterostructure photodetector offers integrated, non-volatile UV detection and in-sensor computing.
  • This approach provides a promising pathway for creating advanced, energy-efficient smart photodetectors.
  • The technology has potential applications in real-time environmental monitoring and industrial diagnostics.