氧化物双介质层忆阻器的设计及应用

doi:10.15541/jim20220760

无机材料学报 ›› 2023, Vol. 38 ›› Issue (4): 387-398.DOI: 10.15541/jim20220760 CSTR: 32189.14.10.15541/jim20220760

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

氧化物双介质层忆阻器的设计及应用

游钧淇¹(), 李策¹, 杨栋梁¹, 孙林锋¹^,²()

1.北京理工大学物理学院, 先进光电量子结构设计与测量教育部重点实验室, 北京 100081
2.北京理工大学长三角研究院, 嘉兴 314019

收稿日期:2022-12-19 修回日期:2023-01-18 出版日期:2023-04-20 网络出版日期:2023-04-18
通讯作者: 孙林锋, 教授. E-mail: sunlinfeng@bit.edu.cn
作者简介:游钧淇(2000-), 男, 硕士研究生. E-mail: 3120221530@bit.edu.cn
基金资助:
北京市自然科学基金重点专题项目(Z210006);国家自然科学基金青年科学基金(12104051)

Double Dielectric Layer Metal-oxide Memristor: Design and Applications

YOU Junqi¹(), LI Ce¹, YANG Dongliang¹, SUN Linfeng¹^,²()

1. MOE Key Laboratory of Advanced Optoetectronic Quantum Architecture and Measurement, School of Physics, Beijing Institute of Technology, Beijing 100081, China
2. Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China

Received:2022-12-19 Revised:2023-01-18 Published:2023-04-20 Online:2023-04-18
Contact: SUN Linfeng, professor. E-mail: sunlinfeng@bit.edu.cn
About author:YOU Junqi (2000-), male, Master candidate. E-mail: 3120221530@bit.edu.cn
Supported by:
Key Research Program of Beijing Natural Science Foundation(Z210006);Young Scientists Fund of the National Natural Science Foundation of China(12104051)

摘要/Abstract

摘要：

忆阻器可以在单一器件上实现存储和计算功能, 成为打破冯·诺依曼瓶颈的核心电子元器件之一。它凭借独特的易失性/非易失性电阻特性, 可以很好地模拟大脑活动中的突触/神经元的功能。此外, 基于金属氧化物的忆阻器与传统的互补金属氧化物半导体(CMOS)工艺兼容, 受到了广泛关注。近年来, 研究提出了多种基于单介质层结构的金属氧化物忆阻器, 但仍然存在高低阻态不稳定、开关电压波动大和循环耐久性差等问题。在此基础上, 研究人员通过在金属氧化物忆阻器中引入双介质层成功优化了忆阻器的性能。本文首先详细介绍了氧化物双介质层忆阻器的优势, 阐述了氧化物双介质层忆阻器的阻变机理和设计思路, 并进一步介绍了氧化物双介质层忆阻器在神经形态计算中的应用。本文将为设计更高性能的氧化物双介质层忆阻器起到一定的启示作用。

关键词: 忆阻器, 突触, 神经元, 神经形态计算, 双介质层金属氧化物, 综述

Abstract:

Memristor, fusing the functions of storage and computing within a single device, is one of the core electronic components to solve the bottleneck of von Neumann architecture. With the unique volatile/non-volatile resistive switching characteristic, memristor can simulate the function of synapses/neurons in brain well. In addition, due to the compatibility with traditional complementary metal-oxide-semiconductor (CMOS) processes, metal-oxide-based memristors have received a lot of attention. In recent years, many kinds of metal-oxide memristors based on single dielectric layer have been proposed. However, there are still some problems such as the instability of switching voltage, fluctuation of high/low resistance state and poor endurance of memristive device. Thus, the researchers have successfully optimized the device performance by introducing the double dielectric layer into the metal-oxide memristors. In this article, we introduce the advantages of double dielectric layers-based metal-oxide memristors, and discuss their mechanism and design of double dielectric layers-based metal-oxide memristors. Eventually, we introduce their potential applications in neuromorphic computing. This review provides some enlightenment on how to design high-performance metal-oxide memristor based on double dielectric layers.

Key words: memristor, synapse, neuron, neuromorphic computing, double dielectric layer metal-oxide, review

中图分类号:

TQ174

游钧淇, 李策, 杨栋梁, 孙林锋. 氧化物双介质层忆阻器的设计及应用[J]. 无机材料学报, 2023, 38(4): 387-398.

YOU Junqi, LI Ce, YANG Dongliang, SUN Linfeng. Double Dielectric Layer Metal-oxide Memristor: Design and Applications[J]. Journal of Inorganic Materials, 2023, 38(4): 387-398.

图/表 10

图1 氧化物双介质层忆阻器与氧化物单介质层忆阻器的结构和性能对比

Fig. 1 Comparison of the structure and performance between the single/double dielectric layer metal-oxide memristor (a, d) Schematic diagrams for (a) single and (d) double dielectric layer metal-oxide memristors; (b, e) Comparison of I-V curves between (b) ZrO2-based memristor and (e) Ta2O5/ZrO2-based memristor with bi-layer structure exhibiting more uniform switching voltage[17]; (c, f) Comparison of the endurance between (c) HfO2-based memristor and (f) HfO2:Al/HfO2-based memristor with double dielectric layer exhibiting better cycling endurance[18]

表1 氧化物单介质层忆阻器与氧化物双介质层忆阻器性能参数对比

Table 1 Performance comparison of the single/double dielectric layer metal-oxide memristors

Memristor structure		Range of Set voltage, ΔV_Set/V	Range of Reset voltage, ΔV_Reset/V	Endurance	On/Off ratio	Retention/s	Ref.
Single dielectric layer	Ta/ZrO₂/TiN	-1.0 ~-1.6 (0.6)	0.8 ~ 1.5 (0.7)	100	10²	-	[15]
	Cu/Al₂O₃/Pt	0.4 ~ 1.2 (0.8)	-0.1 ~-0.8 (0.7)	2×10³	10⁵	10⁵	[19]
	Ag/ZnO/Pt	0.3 ~ 1.0 (0.7)	-0.4 ~-0.8 (0.4)	10²	50	10⁴	[20]
	TaN/Ta₂O₅/Pt	2.0 ~ 4.5 (2.5)	-2.5 ~-4.5 (2)	10⁴	-	10⁴	[21]
	Ta/ZrO₂/Pt	0.4 ~ 2.0 (1.6)	-0.4 ~-1.0 (0.6)	100	-	-	[22]
Double dielectric layer	Ag/SiO₂/Ta₂O₅/Pt	0.14 ~ 0.24 (0.1)	-0.06 ~-0.14 (0.08)	10³	10³	10⁴	[14]
	Ta/ZrO₂/ZTO/TiN	-0.8 ~-1.2 (0.4)	0.8 ~ 1.2 (0.4)	10⁵	10²	3×10³	[15]
	Ta/Ta₂O₅/ZrO₂/Pt	0.7 ~ 1.2 (0.5)	-0.5 ~-0.8 (0.3)	10⁶	10²	10⁴	[17]
	TaN/Ta₂O₅/WO₃/Pt	1.6 ~ 2.3 (0.7)	-1.9 ~-2.5 (0.6)	10⁹	-	10⁶	[21]
	Ti/HfO₂/TiO_x/Pt	-0.8 ~-1.1 (0.3)	1.4 ~ 1.5 (0.1)	10⁷	10³	10⁵	[23]

图2 氧化物双介质层忆阻器在构建神经网络方面的性能优势

Fig. 2 Advantages of the double dielectric layer metal-oxide memristor in building neural network (a) I-V curves of Pt/Al2O3/TaOx/Ta memristor with self-rectifying characteristic[26]; (b) Comparison of the pulse response between the HfO2 and the AlOx/HfO2-based memristor[30]

图3 基于电场局域化效应的氧化物双介质层忆阻器的机制与性能[14]

Fig. 3 Mechanism and characteristic of the double dielectric layer metal-oxide memristor based on the localization effect of electric field[14] (a) Schematic illustration for the switching mechanism of Ag/SiO2/Ta2O5/Pt memristor; (b) I-V characteristic of Ag/SiO2/Ta2O5/Pt memristor

图4 基于氧空位梯度的氧化物双介质层器件的两种机制和性能对比

Fig. 4 Two mechanisms and characteristics comparison of the double dielectric layer metal-oxide memristor based on oxygen vacancy gradient (a, b) Schematic diagrams of the resistance switching mechanism with (a) the structure of W/AlOx/AlOy/Pt memristor[47], (b) Ti/HfO2/TiOx/Pt memristor[23]; (c, d) Endurance of W/AlOx/AlOy/Pt memristor[47] and Ti/HfO2/TiOx/Pt memristor[23], and the Ti/HfO2/TiOx/Pt memristor with transition layer exhibiting more stable resistance states

图5 基于焦耳热效应的氧化物双介质层忆阻器的机制与性能[57]

Fig. 5 Mechanism and performance of the double dielectric layer metal-oxide memristor based on Joule heating effect[57] (a) Schematic diagrams of the switching mechanism of Ta/ZrO2(Y)/Ta2O5/TiN memristor; (b) I-V characteristic of Ta/ZrO2(Y)/Ta2O5/TiN memristor with nonlinear low-resistance state

图6 氧化物双介质层忆阻器实现线性对称的脉冲响应的机制[58]

Fig. 6 Mechanism of the double dielectric layer metal-oxide memristor with the linear symmetrical pulse response[58] (a) Schematic representation of the switching mechanism of Ag/SiO2/VOx/Pt memristor; (b) Pulse response of Ag/SiO2/VOx/Pt memristor represents highly linear and symmetric properties

图7 基于氧化物双介质层的忆阻器实现数据集分类[51]

Fig. 7 Data set classification using memristor based on double dielectric layer metal-oxide[51] (a) Schematic of Pd/TaOx/Ta2O5/Pd memristor crossbar array; (b, c) The initial data and classification results of the data set

图8 氧化物双介质层忆阻器实现语音识别[61]

Fig. 8 Demonstration of speech recognition using double dielectric layer metal-oxide memristor[61] (a) Schematic of the memristor-based reservoir computing system; (b) Diagram of Ti/TiOx/TaOy/Pt memristor structure; (c) Typical audio waveform of digit 9; (d) Recognition error rate of speech varies as a function of the mask length with error bar representing variation between memristor devices

图9 氧化物双介质层忆阻器实现图像识别

Fig. 9 Demonstration of image recognition using double dielectric layer metal-oxide memristor (a) SEM image of the 64×64 memristor crossbar array; (b) All experimental output currents for the digit “7”[59]; (c) Recognition diagrams of conductance and synaptic weights of digit “3”; (d) Evolution of the recognition accuracy of the MNIST under different synaptic coupling and training epochs[62]

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氧化物双介质层忆阻器的设计及应用

Double Dielectric Layer Metal-oxide Memristor: Design and Applications

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