Color‐Recognizing Si‐Based Photonic Synapse for Artificial Visual System

• Published in: Advanced intelligent systems 2020-11, Vol.2 (11), p.n/a
• Main Authors: Li, Dongyang, Li, Chunmei, Ilyas, Nasir, Jiang, Xiangdong, Liu, Fucai, Gu, Deen, Xu, Ming, Jiang, Yadong, Li, Wei
• Format: Article
• Language: English
• Subjects: Amorphous silicon; Artificial vision; Behavior; CMOS; Color; color recognition; Electrodes; Lasers; Learning; Machine vision; neuromorphic behavior; Neuromorphic computing; Pattern recognition; Photoconductivity; photonic synapses; Photonics; Photovoltaic cells; Quantum dots; Recognition; Scanning electron microscopy; Sensory stimulation; Synapses; Vision systems; Visual signals
• ISSN: 2640-4567; 2640-4567
• DOI: 10.1002/aisy.202000107

Recently, photonic synapses that can directly respond to light signals have attracted much attention due to their huge application potential in neuromorphic chips and artificial vision systems. However, the implementation of an artificial visual system based on a synapse remains a considerable challenge due to the limitation that most current photonic synapses fail to recognize color. Here, a photonic synapse with color recognition capability is proposed and demonstrated. Through the light‐induced adjustment of dangling bond defects inside the amorphous silicon (a‐Si) film, the device exhibits switchable volatile and nonvolatile photoconductivity (PC) behaviors at the wavelengths of 635 and 450 nm, respectively. Based on the dual PC, the photonic synapse enables dual synaptic plasticity depending on the stimulation light, allowing not only various synaptic functions, but also learning experiences, associative learning behaviors, and recognition of the red and blue colors. Moreover, the dual synaptic plasticity of the photonic synapse could be modulated via a voltage in the range below ≈1 V to realize the stable detection and precise extraction of the grayscale and color signals. With its simple structure and compatibility with existing Si‐complementary metal oxide semiconductor (CMOS) technology, this photonic synapse shows potential for application in neuromorphic computing and advanced robot vision systems. The photonic synapse demonstrated here exhibits a unique switchable volatile and nonvolatile photoconductive behavior, enabling not only various synaptic functions, but also learning experience, associative learning behavior, and color recognition. The device, with a simple structure and compatibility with Si‐complementary metal oxide semiconductor (CMOS) technology, could be promising for neuromorphic computing application and advanced robot vision systems.