Realize ultralow-energy-consumption photo-synaptic device based on a single(Al,Ga)N nanowire for neuromorphic computing

作     者：Xiushuo Gu Min Zhou Yukun Zhao Qianyi Zhang Jianya Zhang Yonglin Huang Shulong Lu 

作者机构：College of Electronic and Optical Engineering&College of Flexible Electronics(Future Technology)Nanjing University of Posts and TelecommunicationsNanjing 210023China Key Lab of Nanodevices and ApplicationsSuzhou Institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of Sciences(CAS)Suzhou 215123China School of Nano-Tech and Nano-BionicsUniversity of Science and Technology of ChinaHefei 230026China Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy ApplicationSchool of Physical Science and TechnologySuzhou University of Science and TechnologySuzhou 215009China 

出 版 物：《Nano Research》 (纳米研究（英文版）)

年 卷 期：2024年第17卷第3期

页      面：1933-1941页

核心收录：

学科分类：07[理学] 070205[理学-凝聚态物理] 08[工学] 080501[工学-材料物理与化学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：The authors are grateful for the Key Research Program of Frontier Sciences,CAS(No.ZDBS-LY-JSC034) the Research Program of Scientific Instrument and Equipment of CAS(No.YJKYYQ20200073) the National Natural Science Foundation of China(No.62174172) The authors are thankful for the technical support from the Vacuum Interconnected Nanotech Workstation(Nano-X,No.F2309),Platform for Characterization&Test of SINANO,CAS 

主　　题：single(Al Ga)N nanowire light-stimulated synaptic device low-energy-consumption neural network 

摘      要：The rapid development of artificial intelligence poses an urgent need for low-energy-consumption and small-sized artificial photonic ***,it is pretty novel to demonstrate a light-stimulated synaptic device based on a single(Al,Ga)N nanowire *** to the presence of vacancy defects in the single nanowire,the artificial synaptic device can simulate multiple functions of biological synapses under stimulation of both 310 and 365 nm light photons,including paired-pulse facilitation,spike timing dependent plasticity,and memory learning *** energy consumption of artificial synaptic device can be reduced as little as 5.58×10^(-13) J,which is close to that of the biological synapse in human ***,the synaptic device is demonstrated to have the high stability for both long-time stimulation and long-time *** on the experimental conductance of long-term potentiation and long-term depression,the simulated three-layer neural network can achieve a high recognition rate of 92%after only 10 training *** a brain-like behavior,the single-nanowire-based synaptic devices can promote the development of visual neuromorphic computing technology and artificial intelligence systems requiring ultralow energy consumption.