All‐Optically Modulated In‐Sensor Computing Device Based on Ionic‐Conducting CuInP ₂ Se ₆

Abstract

Abstract Inspired by the human visual system, in‐sensor computing has emerged as a promising approach to address growing demands for real‐time image processing while overcoming constraints in computational resources. However, existing in‐sensor computing optoelectronic devices still face challenges such as complex heterostructures or limited optical modulation for operational efficiency, restricting their practical use. Here, a simple two‐terminal optoelectronic device has been fabricated using the 2D material CuInP 2 Se 6 , achieving neuromorphic functionalities through all‐optical modulation. The device exhibits a tunable photoresponse across the visible spectrum (400 to 700 nm) and enables bidirectional conductance modulation in response to light stimuli, driven by the interaction between Cu⁺ ions and photogenerated electrons. It shows high linearity with 300 discrete conductance states under red, green, and blue light, enabling color‐specific image feature extraction, processing, and recognition across three channels. This approach significantly enhances color image recognition accuracy by 4.6% when integrated with a three‐channel convolutional neural network. Additionally, the bidirectional photoresponse allows for efficient noise suppression during color image preprocessing, leading to a 490% improvement in signal‐to‐noise ratio. These findings highlight the potential of CuInP 2 Se 6 ‐based architecture for robust performance, paving the way for in‐sensor neuromorphic vision systems in artificial intelligence and biomimetic computing.