等离子体处理对突触晶体管长程塑性的影响  

Effect of Plasma Treatment on the Long-term Plasticity of Synaptic Transistor

作　　者：邱海洋 苗广潭 李辉[1] 栾奇[1] 刘国侠[1] 单福凯[1] QIU Haiyang;MIAO Guangtan;LI Hui;LUAN Qi;LIU Guoxia;SHAN Fukai(College of Microtechnology&Nanotechnology,Qingdao University,Qingdao 266071,China)

机构地区：[1]青岛大学微纳技术学院,青岛266071

出　　处：《无机材料学报》2023年第4期406-412,共7页Journal of Inorganic Materials

基　　金：国家重点研发计划(2019YE0121800);国家自然科学基金(51872149);山东省自然科学基金(ZR2022MF246)。

摘　　要：作为神经形态计算系统的基本组成单元,人工突触器件在高性能并行计算、人工智能和自适应学习方面具有巨大的应用潜力。其中,电解质栅突触晶体管(Electrolyte-gated synaptic transistors,EGSTs)以其沟道电导的可控性成为下一代神经形态器件被广泛研究的对象,并用来模拟神经突触功能。EGSTs因双电层的快速自放电效应,导致其存在长程塑性持续时间较短和沟道电导不易调控等问题。本研究采用水诱导的In_(2)O_(3)薄膜作为沟道材料,以壳聚糖作为栅电解质材料,制备了基于In_(2)O_(3)的EGSTs,并对器件沟道层进行了氧等离子体处理。研究发现,利用氧等离子体中的活性氧自由基在沟道层表面产生陷阱态,使更多氢离子在电解质/沟道界面处被俘获,器件性能表现为回滞窗口增大,对EGSTs器件的长程塑性实现调控。基于双电层的静电耦合效应和电化学掺杂效应,本研究利用EGSTs器件模拟了神经突触的兴奋性突触后电流(EPSC)、双脉冲易化(PPF)、短程塑性(STP)和长程塑性(LTP)等突触行为。同时,基于该器件的EGSTs增强/抑制特性,采用三层人工神经网络进行手写数字识别,经过仿真训练后,发现该器件可训练出较高的识别率(94.7%)。这些研究结果揭示:表面等离子体处理是影响器件性能的一项关键技术,并证明了该技术对调节EGSTs神经形态器件的突触功能具有较大的应用潜力。As the basic and essential unit of neuromorphic computing system,artificial synaptic devices exhibit great potential in accelerating the high-performance parallel computation,artificial intelligence,and adaptive learning.Among them,electrolyte-gated synaptic transistors(EGSTs)have received increasing attention as the next generation neuromorphic devices owing to its controllable channel conductance.The devices exhibit the abilities of simulating the short-term plasticity(STP)and long-term plasticity(LTP)of the neural synapses.However,most of EGSTs exhibit short persistence for LTP and their channel conductance is difficult to be adjusted due to the rapid self-discharge of the electric double layer.In this work,the EGSTs based on water-induced In_(2)O_(3)as the channel and chitosan as gate electrolyte were constructed and the O_(2)plasma treatments were performed.The formation of traps on the channel surface is caused by the O_(2)plasma treatments,which leads to capturing hydrogen ions at interface of the electrolyte/channel layer,and the device performance exhibits an enlarged hysteresis window,so as to regulate LTP of EGSTs.Biological synaptic functions,including excitatory postsynaptic current(EPSC),paired-pulse facilitation(PPF),STP,and LTP,were mimicked by electrochemical doping and electrostatic coupling effects.Meanwhile,based on the experimentally verified potentiation/depression characteristics of the EGSTs,a three-layer artificial neural network is applied for handwritten digit recognition,and simulation tests can obtain high recognition accuracy of 94.7%.These results reveal that surface plasma treatment is one of the key technologies to affect the device performance,which has great potential in regulating synaptic function of EGSTs.

关 键 词：电解质栅突触晶体管 突触塑性 等离子体处理 模式识别 

分 类 号：TQ174[化学工程—陶瓷工业]