高均一性二维碲化钼忆阻器阵列及其神经形态计算应用

doi:10.15541/jim20210658

无机材料学报 ›› 2022, Vol. 37 ›› Issue (7): 795-801.DOI: 10.15541/jim20210658

所属专题：【信息功能】Max层状材料、MXene及其他二维材料

高均一性二维碲化钼忆阻器阵列及其神经形态计算应用

何慧凯¹(), 杨蕊²^,³(), 夏剑³^,⁴, 王廷泽³^,⁴, 董德泉³^,⁴, 缪向水²^,³

1.中国电子科技南湖研究院, 嘉兴 314002
2.湖北江城实验室, 武汉 430205
3.华中科技大学光学与电子信息学院, 武汉光电国家实验室, 武汉 430074
4.华中科技大学材料科学与工程学院, 材料加工与模具技术国家重点实验室, 武汉 430074

收稿日期:2021-10-25 修回日期:2021-12-14 出版日期:2022-07-20 网络出版日期:2022-01-06
通讯作者: 杨蕊, 教授. E-mail: yangrui@hust.edu.cn
作者简介:何慧凯(1992-), 博士. E-mail: hehk@hust.edu.cn

High-uniformity Memristor Arrays Based on Two-dimensional MoTe₂ for Neuromorphic Computing

HE Huikai¹(), YANG Rui²^,³(), XIA Jian³^,⁴, WANG Tingze³^,⁴, DONG Dequan³^,⁴, MIAO Xiangshui²^,³

1. Nanhu Academy of Electronics and Information Technology, Jiaxing 314002, China
2. Hubei Yangtze Memory Laboratories, Wuhan 430205, China
3. Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
4. State Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Received:2021-10-25 Revised:2021-12-14 Published:2022-07-20 Online:2022-01-06
Contact: YANG Rui, professor. E-mail: yangrui@hust.edu.cn
About author:HE Huikai (1992-), PhD. E-mail: hehk@hust.edu.cn
Supported by:
National Natural Science Foundation of China(U1832116);National Natural Science Foundation of China(51772112)

摘要/Abstract

摘要：

二维过渡金属硫化合物是构建纳米电子器件的理想材料, 基于该材料体系开发用于信息存储和神经形态计算的忆阻器, 受到了学术界的广泛关注。受制于低成品率和低均一性问题, 二维过渡金属硫化合物忆阻器阵列鲜见报道。本研究采用化学气相沉积得到厘米级二维碲化钼薄膜, 并通过湿法转移和剥离工艺制备得到碲化钼忆阻器件。该碲化钼器件表现出优异的保持性(保持时间>500 s)、快速的阻变(SET时间~60 ns, RESET时间~280 ns)和较好的循环寿命(阻变2000圈后仍可正常工作)。该器件具有高成品率(96%)、低阻变循环间差异性(SET过程为6.6%, RESET过程为5.2%)和低器件间差异性(SET过程为19.9%, RESET过程为15.6%)。本工作成功制备出基于MoTe₂的3×3忆阻器阵列。在此基础上, 将研制的MoTe₂器件用于手写体识别, 实现了91.3%的识别率。最后, 通过对MoTe₂器件高低阻态的电子输运机制进行拟合分析, 揭示了该器件阻变源于类金属导电细丝的通断过程。本项工作表明大尺寸二维过渡金属硫化合物在未来神经形态计算中具有巨大的应用潜力。

关键词: 二维材料, 碲化钼, 忆阻器阵列, 神经形态计算

Abstract:

Two-dimensional transition metal dichalcogenides are appealing materials for the preparation of nanoelectronic devices, and the development of memristors for information storage and neuromorphic computing using such materials is of particular interest. However, memristor arrays based on two-dimensional transition metal dichalcogenides are rarely reported due to low yield and high device-to-device variability. Herein, the 2D MoTe₂ film was prepared by the chemical vapor deposition method. Then the memristive devices based on 2D MoTe₂ film were fabricated through the polymethyl methacrylate transfer method and the lift-off process. The as-prepared MoTe₂ devices perform stable bipolar resistive switching, including superior retention characteristics (>500 s), fast switching (~60 ns for SET and ~280 ns for RESET), and excellent endurance (>2000 cycles). More importantly, the MoTe₂ devices exhibit high yield (96%), low cycle-to-cycle variability (6.6% for SET and 5.2% for RESET), and low device-to-device variability (19.9% for SET and 15.6% for RESET). In addition, a 3×3 memristor array with 1R scheme is successfully demonstrated based on 2D MoTe₂ film. And, high recognition accuracy (91.3%) is realized by simulation in the artificial neural network with the MoTe₂ devices working as synapses. It is found that the formation/rupture of metallic filaments is the dominating switching mechanism based on the investigations of the electron transport characteristics of high and low resistance states in the present MoTe₂ devices. This work demonstrates that large-scale two-dimensional transition metal dichalcogenides film is of great potential for future applications in neuromorphic computing.

Key words: two-dimensional material, MoTe₂, memristor array, neuromorphic computing

中图分类号:

TQ125

何慧凯, 杨蕊, 夏剑, 王廷泽, 董德泉, 缪向水. 高均一性二维碲化钼忆阻器阵列及其神经形态计算应用[J]. 无机材料学报, 2022, 37(7): 795-801.

HE Huikai, YANG Rui, XIA Jian, WANG Tingze, DONG Dequan, MIAO Xiangshui. High-uniformity Memristor Arrays Based on Two-dimensional MoTe₂ for Neuromorphic Computing[J]. Journal of Inorganic Materials, 2022, 37(7): 795-801.

图/表 20

Fig. S1 PMMA transfer method

Fig. 1 Characterization of MoTe2 film and electrical measurement of Au/Ti/MoTe2/Au/Ti device (a) Photo of the centimeter-scale MoTe2 film; (b) Raman spectrum of the MoTe2 film; (c) Optical image of the prepared memristive devices with the structure of Au/Ti/MoTe2/Au/Ti; (d) Optical image of a 3×3 memristor array

Fig. S2 XRD pattern of the MoTe2 film

Fig. S3 Fabrication process of the Au/Ti/MoTe2/Au/Ti device

Fig. S4 AFM image (a) of 3×3 memristor array, and the height profile (b) along the horizontal line and the vertical line

Fig. S5 Electroforming process of the device

Fig. 2 Stable bipolar resistive switching behavior and retention characteristics of the MoTe2 device (a) 20 cycles of I-V curves with a compliance current of 3 mA; (b) Retention characteristics of the HRS and the LRS read at 0.1 V

Fig. 3 Fast switching and good endurance of the MoTe2 device (a) SET speed under the pulse with the amplitude 1.3 V; (b) RESET speed of the MoTe2 device under the pulse with the amplitude of -1.0 V; (c) Over 2000 switching cycles obtained by applying SET pulse of 1.7 V/700 ns and RESET pulse of -1.2 V/7 μs Colorful figures are available on website

Fig. S6 I-V curves of 24 Au/Ti/MoTe2/Au/Ti devices All devices show stable resistive switching with low cycle-to-cycle and device-to-device variability

Fig. 4 Cumulative distribution of (a) VSET and (b) VRESET of 24 devices

Fig. S7 Cumulative distribution of device (a) HRS and (b) LRS of 24 devices

Fig. S8 Estimation of the array size for the prepared CVD-MoTe2 device (a) Sneak current path at read in a square crossbar array where all bits except the selected one are at LRS, and the equivalent circuit can be represented by three resistors (region 1, region 2 and region 3); (b) Dependence of the read margin on the crossbar line number for both 1R and 1T1R schemes

Fig. S9 I-V characteristics of the Pt/TaOx/TiO2/TaOx/Pt selector[4]

Fig. 5 Stable resistive switching of the MoTe2 array device after electroforming process (a) Electroforming process of the MoTe2 array device; (b) 20 cycles I-V curves of the MoTe2 array device with a compliance current of 5 Ma

Fig. S10 I-V curves of 9 devices in 3×3 array

Fig. S11 Long-term potentiation and depression of the device using 50 potentiation (1 V, 500 ns) and depression (-1 V, 5 µs) presynaptic pulses

Fig. 6 Potentiation and depression processes of the present device Circles are experimental results, red lines are fitting results with a phenomenological model $G=a+c{{e}^{-\beta N}}$

Fig. 7 Recognition accuracy for small and large handwritten digit images with experimental devices and ideal numeric Colorful figures are available on website

Fig. 8 Mechanism analysis of the memristive behavior in the MoTe2 device (a) I-V characteristics at HRS under different temperatures, with current increasing as the temperature increases Fitted data using the Schottky emission model for HRS is shown in the inset; (b) I-V characteristics at LRS at different temperatures, with current decreasing as the temperature increase, indicating a metallic characteristic

Table 1 Key resistance values and the corresponding maximum number of word lines/bit lines (N) with read margin >10%

Scheme	$R_{\text{LRS}}^{\text{select}}$/Ω	$R_{\text{HRS}}^{\text{select}}$/Ω	$R_{\text{LRS}}^{\text{sneak}}$/Ω	N
1R	150	1500	150	4
1S1R	350	1700	1.25×10⁵	870

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高均一性二维碲化钼忆阻器阵列及其神经形态计算应用

High-uniformity Memristor Arrays Based on Two-dimensional MoTe₂ for Neuromorphic Computing

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高均一性二维碲化钼忆阻器阵列及其神经形态计算应用

High-uniformity Memristor Arrays Based on Two-dimensional MoTe2 for Neuromorphic Computing

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High-uniformity Memristor Arrays Based on Two-dimensional MoTe₂ for Neuromorphic Computing