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Related Concept Videos

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There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
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Infrared In-Sensor Computing with ReSe2 Photoelectric Memristor Arrays.

Chenxu Sheng1, Shuwen Shen1, Peilin Sun1

  • 1School of Information Science and Technology, Fudan University, Shanghai 200433, China.

ACS Applied Materials & Interfaces
|April 17, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an infrared in-sensor computing platform using a ferroelectric memristor array. This integrated system enables efficient, low-latency infrared image sensing and recognition, paving the way for advanced intelligent vision hardware.

Keywords:
ReSe2ferroelectric materialinfrared in-sensor computingphotoelectric memristor crossbar arrayself-powered photoresponse

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Area of Science:

  • Materials Science
  • Electrical Engineering
  • Computer Science

Background:

  • Infrared (IR) vision is crucial for sensing in challenging conditions where visible light fails.
  • Current IR systems suffer from high data transfer overhead, latency, and energy use due to separated sensing, memory, and computation.
  • There is a need for integrated, efficient IR sensing and processing solutions.

Purpose of the Study:

  • To develop an infrared in-sensor computing platform.
  • To integrate IR sensing, nonvolatile memory, and computation into a single system.
  • To demonstrate a practical pathway for compact, low-latency, and energy-efficient intelligent vision hardware.

Main Methods:

  • Developed a ferroelectric photoelectric memristor array using a ReSe2 channel and in-plane ferroelectric polarization.
  • Engineered devices with highly linear, nonvolatile, and multilevel modulation of self-powered photoresponsivity.
  • Utilized a 5x9 photoelectric memristor crossbar array for direct IR image sensing and processing.

Main Results:

  • Achieved stable analog photoelectric weight programming with near-infrared sensitivity.
  • Demonstrated proof-of-concept IR image recognition with in situ sensing and classification.
  • Attained high recognition accuracy and robust classification margins, even with noise, without external computation.

Conclusions:

  • The developed platform integrates IR sensing, memory, and computation efficiently.
  • This work presents a viable approach for next-generation intelligent vision systems.
  • The in-sensor computing platform offers significant advantages in latency and energy consumption for IR applications.