Wavelength‐Selective Photodetector and Neuromorphic Visual Sensor Utilizing Intrinsic Defect Semiconductor

With the rapid developments of Artificial Intelligence (AI) and the Internet of Things (IoT), increasingly intricate and expanding application scenarios are placing higher demands on current machine vision capabilities. Therefore, there is a pressing need to simultaneously achieve diverse functionalities, simple designs, and efficient computing in vision devices. Here, the study develops a two‐terminal optoelectronic device utilizing a single 2D intrinsic defect semiconductor In2S3. The device demonstrates wavelength‐selective photodetection and neuromorphic visual capabilities, attributed to defect‐related charge‐trapping/de‐trapping processes. As a photodetector, the device exhibits a high photoresponsivity of 473.6 A W−1, a high external quantum efficiency of 1.6 × 105%, and a fast rise/fall time of 0.3/1.4 ms at the wavelength of 359 nm. As an all‐in‐one neuromorphic visual device, optoelectronic‐driven fundamental synaptic functions, including paired‐pulse facilitation (PPF), short‐term plasticity (STP), long‐term plasticity (LTP), and “learning‐experience”, are successfully mimicked at the wavelength of 671 nm. Moreover, one‐shot recognition of the 12‐letter image “SHAN XI NORMAL” is achieved through an artificial convolutional neural network. This study provides a new strategy for developing compact high‐level intelligence systems for complex application scenarios. A wavelength‐selective artificial vision system based on intrinsic defect semiconductor In2S3 transistor is reported. The device exhibits excellent photodetection capability and fast response time at a wavelength of 359 nm. Neuromorphic visual sensor with integrated sensing, memory, and computing is successfully demonstrated at a wavelength of 671 nm, exhibiting highly parallel processing of large‐scale information.