等离子体处理对突触晶体管长程塑性的影响

doi:10.15541/jim20220675

无机材料学报 ›› 2023, Vol. 38 ›› Issue (4): 406-412.DOI: 10.15541/jim20220675 CSTR: 32189.14.10.15541/jim20220675

所属专题：【信息功能】忆阻器材料与器件(202506)

• 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()

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()

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/Abstract

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 O₂plasma treatments were performed. The formation of traps on the channel surface is caused by the O₂plasma 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

中图分类号:

TQ174

邱海洋, 苗广潭, 李辉, 栾奇, 刘国侠, 单福凯. 等离子体处理对突触晶体管长程塑性的影响[J]. 无机材料学报, 2023, 38(4): 406-412.

QIU Haiyang, MIAO Guangtan, LI Hui, LUAN Qi, LIU Guoxia, SHAN Fukai. Effect of Plasma Treatment on the Long-term Plasticity of Synaptic Transistor[J]. Journal of Inorganic Materials, 2023, 38(4): 406-412.

图/表 5

图1 未经处理(a)和经过等离子体处理(b) In2O3薄膜的AFM图片

Fig. 1 AFM images of (a) untreated and (b) plasma-treated In2O3 films

图2 突触晶体管的示意图和器件性能

Fig. 2 Schematic illustration and properties of synaptic transistor (a) Schematic illustration of a synapse; (b) Device structure; (c) Frequency-dependent characteristics of chitosan electrolyte with inset showing device configuration for C-F measurement; (d) Transfer curves of untreated and O2 plasma-treated (W/O2 plasma) device; (e) Output curves of untreated device; (f) Output curves of O2 plasma treated device

图3 未经处理和经氧等离子体处理的器件短程塑性(a)和长程塑性(b), 处理前后器件的PPF曲线(c)及PPF指数随脉冲间隔的变化(d)

Fig. 3 STP (a) and LTP (b) characteristics of untreated and O2 plasma-treated (W/O2 plasma) device, (c) paired-pulse facilitation curves for device with and without O2 plasma treatment and (d) PPF index as a function of pulse interval Colorful figures are available on website

图4 未经处理(a)和经氧等离子体处理(c)器件增强/抑制特性。经过50次循环后, 未经处理(b)和经氧气等离子体处理(d)器件P-D曲线的循环稳定性

Fig. 4 Potentiation/depression characteristics of untreated (a) and O2 plasma-treated (c) devices, repeatability, and stability of P-D curves after 50 cycles of untreated (b) and O2 plasma-treated (d) devices

图5 人工神经网络、突触权重交叉阵列的硬件和监督学习结果检验

Fig. 5 Artificial neural network, synaptic weight cross array of hardware and supervised learning outcome tests (a) Diagram of the ANN for pattern recognition; (b) Schematic diagram showing a hardware implemented synaptic weight cross-bar array with EGSTs with evolution classification accuracy as a function of training epochs for small digits (c), large digits (d), and file types datasets (e), respectively Colorful figures are available on website

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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

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