Journal of Inorganic Materials ›› 2023, Vol. 38 ›› Issue (4): 387-398.DOI: 10.15541/jim20220760

• Topical Section on Neuromorphic Materials and Devices (Contributing Editor: WAN Qing) • Previous Articles     Next Articles

Double Dielectric Layer Metal-oxide Memristor: Design and Applications

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

  1. 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:
  • About author:YOU Junqi (2000-), male, Master candidate. E-mail:
  • Supported by:
    Key Research Program of Beijing Natural Science Foundation(Z210006);Young Scientists Fund of the National Natural Science Foundation of China(12104051)


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

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