Статья

Robust Ag/ZrO<sub>2</sub>/WS<sub>2</sub>/Pt Memristor for Neuromorphic Computing

Xiaobing YanDepartment of Materials Science and Engineering, National University of Singapore, Singapore 117576, SingaporeCuiya QinNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaChao LüDepartment of Electrical and Computer Engineering, Southern Illinois University Carbondale, Carbondale, Illinois 62901, United StatesJianhui ZhaoNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaRujie ZhaoDepartment of Electrical and Computer Engineering, Southern Illinois University Carbondale, Carbondale, Illinois 62901, United StatesDeliang RenNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaZhenyu ZhouNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaHong WangNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaJingjuan WangNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaLei ZhangNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaXiaoyan LiNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaYifei PeiNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaGong WangNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaQianlong ZhaoNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaKaiyang WangNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaZuoao XiaoNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. ChinaHui LiNational-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding 071002, P. R. China

2019en

ABI

Аннотация

The development of the information age has made resistive random access memory (RRAM) a critical nanoscale memristor device (MD). However, due to the randomness of the area formed by the conductive filaments (CFs), the RRAM MD still suffers from a problem of insufficient reliability. In this study, the memristor of Ag/ZrO2/WS2/Pt structure is proposed for the first time, and a layer of two-dimensional (2D) WS2 nanosheets was inserted into the MD to form 2D material and oxide double-layer MD (2DOMD) to improve the reliability of single-layer devices. The results indicate that the electrochemical metallization memory cell exhibits a highly stable memristive switching and concentrated ON- and OFF-state voltage distribution, high speed (∼10 ns), and robust endurance (>109 cycles). This result is superior to MDs with a single-layer ZrO2 or WS2 film because two layers have different ion transport rates, thereby limiting the rupture/rejuvenation of CFs to the bilayer interface region, which can greatly reduce the randomness of CFs in MDs. Moreover, we used the handwritten recognition dataset (i.e., the Modified National Institute of Standards and Technology (MNIST) database) for neuromorphic simulations. Furthermore, biosynaptic functions and plasticity, including spike-timing-dependent plasticity and paired-pulse facilitation, have been successfully achieved. By incorporating 2D materials and oxides into a double-layer MD, the practical application of RRAM MD can be significantly enhanced to facilitate the development of artificial synapses for brain-enhanced computing systems in the future.

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Идентификаторы

DOI: 10.1021/acsami.9b17160

Цитирования и источники

Цитирований: 4Использованных источников: 0

Показатели — AkademScholar