无机材料学报 ›› 2023, Vol. 38 ›› Issue (4): 406-412.DOI: 10.15541/jim20220675

• 专栏:神经形态材料与器件(特邀编辑:万青) • 上一篇    下一篇

等离子体处理对突触晶体管长程塑性的影响

邱海洋(), 苗广潭, 李辉, 栾奇, 刘国侠, 单福凯()   

  1. 青岛大学 微纳技术学院, 青岛 266071
  • 收稿日期:2022-11-14 修回日期:2022-12-19 出版日期:2023-04-20 网络出版日期:2022-12-28
  • 通讯作者: 单福凯, 教授. E-mail: fkshan@qdu.edu.cn
  • 作者简介:邱海洋(1997-), 男, 硕士研究生. E-mail: 17853260598@163.com
  • 基金资助:
    国家重点研发计划(2019YE0121800);国家自然科学基金项目(51872149);山东省自然科学基金(ZR2022MF246)

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

QIU Haiyang(), MIAO Guangtan, LI Hui, LUAN Qi, LIU Guoxia, SHAN Fukai()   

  1. College of Microtechnology & Nanotechnology, Qingdao University, Qingdao 266071, China
  • Received:2022-11-14 Revised:2022-12-19 Published:2023-04-20 Online:2022-12-28
  • Contact: SHAN Fukai, professor. E-mail: fkshan@qdu.edu.cn
  • About author:QIU Haiyang (1997-), male, Master candidate. E-mail: 17853260598@163.com
  • Supported by:
    National Key Research and Development Program(2019YE0121800);National Natural Science Foundation of China(51872149);Natural Science Foundation of Shandong Province(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In2O3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In2O3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。

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

Abstract:

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 In2O3 as the channel and chitosan as gate electrolyte were constructed and the O2 plasma treatments were performed. The formation of traps on the channel surface is caused by the O2 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.

Key words: electrolyte-gated synaptic transistor, synaptic plasticity, plasma treatment, pattern recognition

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