Optically Readable Organic Electrochemical Synaptic Transistors for Neuromorphic Photonic Image Processing
Yunchao Xu, Yiming Shi, Chuan Qian, Pengshan Xie, Chenxing Jin, Xiaofang Shi, Gengming Zhang, Wanrong Liu, Changjin Wan, Johnny C. Ho, Jia Sun, Junliang Yang
Abstract
Optically readable organic synaptic devices have great potential in both artificial intelligence and photonic neuromorphic computing. Herein, a novel optically readable organic electrochemical synaptic transistor (OR-OEST) strategy is first proposed. The electrochemical doping mechanism of the device was systematically investigated, and the basic biological synaptic behaviors that can be read by optical means are successfully achieved. Furthermore, the flexible OR-OESTs are capable of electrically switching the transparency of semiconductor channel materials in a nonvolatile manner, and thus the multilevel memory can be achieved through optical readout. Finally, the OR-OESTs are developed for the preprocessing of photonic images, such as contrast enhancement and denoising, and feeding the processed images into an artificial neural network, achieving a recognition rate of over 90%. Overall, this work provides a new strategy for the implementation of photonic neuromorphic systems.