Investigation of NbOx-based volatile switching device with self-rectifying characteristics

Fang, Yichen; Wang, Zongwei; Cheng, Caidie; Yu, Zhizhen; Zhang, Teng; Yang, Yuchao; Cai, Yimao; Huang, Ru

doi:10.1007/s11432-019-9894-0

Cited by 17 publications

(5 citation statements)

References 7 publications

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“…127 Another type of selector shows typical nonlinear I-V characteristics, which originates from electronic conduction dominated either by a contact barrier or a tunneling barrier. [128][129][130] Interestingly, RRAM with inherent nonlinearity can serve as a self-selection device. With this feature, the device has the advantages of avoiding the characteristics mismatch between the selector and RRAM.…”

Section: Selection Devicementioning

confidence: 99%

“…The TS behavior is demonstrated based on different physical mechanisms with a variety of materials (Figure B‐E), such as insulator‐metal‐transition (IMT), mixed‐ionic‐electronic conduction (MIEC), and ovonic threshold switching (OTS) . Another type of selector shows typical nonlinear I‐V characteristics, which originates from electronic conduction dominated either by a contact barrier or a tunneling barrier . Interestingly, RRAM with inherent nonlinearity can serve as a self‐selection device.…”

Section: High‐speed and Scalable Rram Cells And Systemsmentioning

confidence: 99%

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Memory materials and devices: From concept to application

Zhang

Wang

Shi

et al. 2020

InfoMat

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211

142

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Memory cells have always been an important element of information technology. With emerging technologies like big data and cloud computing, the scale and complexity of data storage has reached an unprecedented peak with a much higher requirement for memory technology. As is well known, better data storage is mostly achieved by miniaturization. However, as the size of the memory device is reduced, a series of problems, such as drain gate‐induced leakage, greatly hinder the performance of memory units. To meet the increasing demands of information technology, novel and high‐performance memory is urgently needed. Fortunately, emerging memory technologies are expected to improve memory performance and drive the information revolution. This review will focus on the progress of several emerging memory technologies, including two‐dimensional material‐based memories, resistance random access memory (RRAM), magnetic random access memory (MRAM), and phase‐change random access memory (PCRAM). Advantages, mechanisms, and applications of these diverse memory technologies will be discussed in this review.

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Section: Selection Devicementioning

confidence: 99%

Section: High‐speed and Scalable Rram Cells And Systemsmentioning

confidence: 99%

Memory materials and devices: From concept to application

Zhang

Wang

Shi

et al. 2020

InfoMat

Self Cite

211

142

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“…Another class of the phase-change device in a broad sense is Mott memristor, which is shown in Figure 3b, and typical material systems include VO x and NbO x . [58][59][60] The Mott memristor such as NbO x device can be regarded as an extended memristor by specifying temperature T as its internal variable, [24,61] which is expressed as…”

Section: Phase-change Memristormentioning

confidence: 99%

Nonlinearity in Memristors for Neuromorphic Dynamic Systems

Yang

Huang

et al. 2021

Small Science

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As semiconductor technology enters the more than Moore era, there exists an apparent contradiction between the rapidly growing demands for data processing and the visible inefficiency rooted in traditional computing architecture. Neuromorphic systems hold great prospects in enabling a new generation of computing paradigm that can address this issue, which demands device components with rich dynamics and nonlinearity. Herein, the nonlinearity in memristive devices and their application in building neuromorphic dynamic systems are reviewed. The internal mechanisms that endow memristive devices with nonlinearity and rich dynamics are reviewed and subsequently the nonlinear spiking neurons that are implemented utilizing the physical processes in memristors are shown. Typical examples on neuromorphic dynamic systems based on nonlinear memristors are summarized, including memristive reservoir, memristive oscillatory neural network, and memristive chaotic computing. Finally, an outlook in the development of neuromorphic dynamic systems is given.

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“…NbO x -based devices that exhibit either threshold or memory resistance switching (RS), according to the content of oxygen vacancies in the NbO x film [ 11 ], can self-assemble as 1Selector-1RRAM (1S1R) devices to suppress crosstalk current. Several studies have reported the threshold switching characteristics of NbO x devices [ 12 , 13 , 14 ], but few studies have investigated the optimization of NbO x memory RS characteristics [ 15 , 16 ]. The performance of NbO x memristor devices is insufficient for applications; thus, it is essential to optimize the performances of NbO x memristor devices.…”

Section: Introductionmentioning

confidence: 99%

Improved Performance of NbOx Resistive Switching Memory by In-Situ N Doping

Zhu

Liu

et al. 2022

Nanomaterials

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Valence change memory (VCM) attracts numerous attention in memory applications, due to its high stability and low energy consumption. However, owing to the low on/off ratio of VCM, increasing the difficulty of information identification hinders the development of memory applications. We prepared N-doped NbOx:N films (thickness = approximately 15 nm) by pulsed laser deposition at 200 °C. N-doping significantly improved the on/off ratio, retention time, and stability of the Pt/NbOx:N/Pt devices, thus improving the stability of data storage. The Pt/NbOx:N/Pt devices also achieved lower and centralized switching voltage distribution. The improved performance was mainly attributed to the formation of oxygen vacancy (VO) + 2N clusters, which greatly reduced the ionic conductivity and total energy of the system, thus increasing the on/off ratio and stability. Moreover, because of the presence of Vo + 2N clusters, the conductive filaments grew in more localized directions, which led to a concentrated distribution of SET and RESET voltages. Thus, in situ N-doping is a novel and effective approach to optimize device performances for better information storage and logic circuit applications.

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Investigation of NbOx-based volatile switching device with self-rectifying characteristics

Cited by 17 publications

References 7 publications

Memory materials and devices: From concept to application

Memory materials and devices: From concept to application

Nonlinearity in Memristors for Neuromorphic Dynamic Systems

Improved Performance of NbOx Resistive Switching Memory by In-Situ N Doping

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