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All-Optically Modulated In-Sensor Computing Device Based on Ionic-Conducting CuInP₂Se₆.

Qianyi Yang^1,2, Yezhao Zhuang^1,2, Zhipeng Zhong^1,2

¹State Key Laboratory of Photovoltaic Science and Technology, Shanghai Frontiers Science Research Base of Intelligent Optoelectronic and Perception, Institute of Optoelectronic and Department of Materials Science, Fudan University, Shanghai, 200433, China.

Advanced Materials (Deerfield Beach, Fla.)

|May 15, 2025

Summary

A new optoelectronic device using 2D CuInP2Se6 enables in-sensor computing for real-time image processing. This neuromorphic vision system achieves high accuracy in color image recognition and noise suppression.

Keywords:

All‐optical modulation In‐sensor computing Ion‐conducting Optoelectronics Synaptic devices

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Area of Science:

Materials Science
Optoelectronics
Artificial Intelligence

Background:

In-sensor computing, inspired by the human visual system, aims to enhance real-time image processing efficiency.
Existing optoelectronic devices face limitations in heterostructure complexity and optical modulation, hindering practical applications.

Purpose of the Study:

To develop a simple, efficient in-sensor computing device for neuromorphic vision.
To explore the potential of 2D CuInP2Se6 for all-optical modulation and advanced image processing.

Main Methods:

Fabrication of a two-terminal optoelectronic device using 2D CuInP2Se6.
Characterization of the device's tunable photoresponse across the visible spectrum (400-700 nm).
Evaluation of bidirectional conductance modulation driven by Cu+ ions and photogenerated electrons.

Main Results:

The device demonstrated 300 discrete, linear conductance states under red, green, and blue light.
Achieved color-specific image feature extraction, processing, and recognition across three channels.
Enhanced color image recognition accuracy by 4.6% when integrated with a convolutional neural network.
Improved signal-to-noise ratio by 490% for color image preprocessing via bidirectional photoresponse.

Conclusions:

CuInP2Se6-based devices offer a simple yet effective architecture for in-sensor neuromorphic vision.
The developed device shows robust performance for artificial intelligence and biomimetic computing applications.
This work paves the way for advanced, low-power visual processing systems.