A Reconfigurable All-Optical-Controlled Synaptic Device for Neuromorphic Computing Applications

神经形态工程学 光刺激 材料科学 计算机科学 背景(考古学) 异质结 光电子学 神经科学 人工神经网络 人工智能 生物 古生物学
作者
Tao Zhang,Chao Fan,Lingxiang Hu,Fei Zhuge,Xinhua Pan,Zhizhen Ye
出处
期刊:ACS Nano [American Chemical Society]
卷期号:18 (25): 16236-16247 被引量:9
标识
DOI:10.1021/acsnano.4c02278
摘要

Retina-inspired visual sensors play a crucial role in the realization of neuromorphic visual systems. Nevertheless, significant obstacles persist in the pursuit of achieving bidirectional synaptic behavior and attaining high performance in the context of photostimulation. In this study, we propose a reconfigurable all-optical controlled synaptic device based on the IGZO/SnO/SnS heterostructure, which integrates sensing, storage and processing functions. Relying on the simple heterojunction stack structure and the role of energy band engineering, synaptic excitatory and inhibitory behaviors can be observed under the light stimulation of ultraviolet (266 nm) and visible light (405, 520 and 658 nm) without additional voltage modulation. In particular, junction field-effect transistors based on the IGZO/SnO/SnS heterostructure were fabricated to elucidate the underlying bidirectional photoresponse mechanism. In addition to optical signal processing, an artificial neural network simulator based on the optoelectrical synapse was trained and recognized handwritten numerals with a recognition rate of 91%. Furthermore, we prepared an 8 × 8 optoelectrical synaptic array and successfully demonstrated the process of perception and memory for image recognition in the human brain, as well as simulated the situation of damage to the retina by ultraviolet light. This work provides an effective strategy for the development of high-performance all-optical controlled optoelectronic synapses and a practical approach to the design of multifunctional artificial neural vision systems.
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