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Memristive Materials and Devices
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Memristive Materials and Devices

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Optical and Photonic Materials".

Deadline for manuscript submissions: closed (20 August 2023) | Viewed by 7150

Special Issue Editor

Prof. Dr. Xiaoning Zhao

E-Mail Website
Guest Editor
Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education, Northeast Normal University, Changchun 130024, China
Interests: memristor; resistive switching; memory; artificial synapses; in-memory computing; neuromorphic computing

Special Issue Information

Dear Colleagues,

With the rapid development of information technology, computing systems with low energy consumption and high processing speed are in great demand. Conventional computing architectures are now facing a von Neumann bottleneck due to the separation of memory and processor. New materials, devices, and architectures are being aggressively studied to meet future computing needs.

Memristive devices, also known as resistive switching devices, have attracted intensive attention due to their simple structure, high switching speed, low power consumption, and desirable switching dynamics for emulating biological synapses. These features make the devices a good candidate for broad applications of nonvolatile memory, logic, in-memory computing, and neuromorphic computing. Over the past decade, a number of studies on memristive devices related to materials, mechanisms, performance, and their neuromorphic applications have been reported.

This Special Issue aims to compile recent developments in the field of memristive materials and devices. The articles presented in this Special Issue will cover various topics, ranging from but not limited to the development of memristive materials, the study of memristive mechanisms, the optimization of memristive performance, and the functionalization of memristive devices.

I kindly invite you to submit a manuscript to this Special Issue. Full papers, communications, and reviews are all welcome.

Prof. Dr. Xiaoning Zhao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • memristor
  • resistive switching
  • artificial synapses
  • in-memory computing
  • neuromorphic computing

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Published Papers (4 papers)

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Research

11 pages, 3743 KiB  
Article
Improved Uniformity of TaOx-Based Resistive Switching Memory Device by Inserting Thin SiO2 Layer for Neuromorphic System
by Dongyeol Ju, Sunghun Kim, Junwon Jang and Sungjun Kim
Materials 2023, 16(18), 6136; https://doi.org/10.3390/ma16186136 - 9 Sep 2023
Cited by 2 | Viewed by 1063
Abstract
RRAM devices operating based on the creation of conductive filaments via the migration of oxygen vacancies are widely studied as promising candidates for next-generation memory devices due to their superior memory characteristics. However, the issues of variation in the resistance state and operating [...] Read more.
RRAM devices operating based on the creation of conductive filaments via the migration of oxygen vacancies are widely studied as promising candidates for next-generation memory devices due to their superior memory characteristics. However, the issues of variation in the resistance state and operating voltage remain key issues that must be addressed. In this study, we propose a TaOx/SiO2 bilayer device, where the inserted SiO2 layer localizes the conductive path, improving uniformity during cycle-to-cycle endurance and retention. Transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS) confirm the device structure and chemical properties. In addition, various electric pulses are used to investigate the neuromorphic system properties of the device, revealing its good potential for future memory device applications. Full article
(This article belongs to the Special Issue Memristive Materials and Devices)
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8 pages, 997 KiB  
Article
A Unified Current-Voltage Model for Metal Oxide-Based Resistive Random-Access Memory
by Harry Chung, Hyungsoon Shin, Jisun Park and Wookyung Sun
Materials 2023, 16(1), 182; https://doi.org/10.3390/ma16010182 - 25 Dec 2022
Cited by 2 | Viewed by 1238
Abstract
Resistive random-access memory (RRAM) is essential for developing neuromorphic devices, and it is still a competitive candidate for future memory devices. In this paper, a unified model is proposed to describe the entire electrical characteristics of RRAM devices, which exhibit two different resistive [...] Read more.
Resistive random-access memory (RRAM) is essential for developing neuromorphic devices, and it is still a competitive candidate for future memory devices. In this paper, a unified model is proposed to describe the entire electrical characteristics of RRAM devices, which exhibit two different resistive switching phenomena. To enhance the performance of the model by reflecting the physical properties such as the length index of the undoped area during the switching operation, the Voltage ThrEshold Adaptive Memristor (VTEAM) model and the tungsten-based model are combined to represent two different resistive switching phenomena. The accuracy of the I–V relationship curve tails of the device is improved significantly by adjusting the ranges of unified internal state variables. Furthermore, the unified model describes a variety of electrical characteristics and yields continuous results by using the device’s current-voltage relationship without dividing its fitting conditions. The unified model describes the optimized electrical characteristics that reflect the electrical behavior of the device. Full article
(This article belongs to the Special Issue Memristive Materials and Devices)
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9 pages, 2744 KiB  
Article
Non-Volatile Memory and Synaptic Characteristics of TiN/CeOx/Pt RRAM Devices
by Hoesung Ha, Juyeong Pyo, Yunseok Lee and Sungjun Kim
Materials 2022, 15(24), 9087; https://doi.org/10.3390/ma15249087 - 19 Dec 2022
Cited by 7 | Viewed by 2174
Abstract
In this study, we investigate the synaptic characteristics and the non-volatile memory characteristics of TiN/CeOx/Pt RRAM devices for a neuromorphic system. The thickness and chemical properties of the CeOx are confirmed through TEM, EDS, and XPS analysis. A lot of [...] Read more.
In this study, we investigate the synaptic characteristics and the non-volatile memory characteristics of TiN/CeOx/Pt RRAM devices for a neuromorphic system. The thickness and chemical properties of the CeOx are confirmed through TEM, EDS, and XPS analysis. A lot of oxygen vacancies (ions) in CeOx film enhance resistive switching. The stable bipolar resistive switching characteristics, endurance cycling (>100 cycles), and non-volatile properties in the retention test (>10,000 s) are assessed through DC sweep. The filamentary switching model and Schottky emission-based conduction model are presented for TiN/CeOx/Pt RRAM devices in the LRS and HRS. The compliance current (1~5 mA) and reset stop voltage (−1.3~−2.2 V) are used in the set and reset processes, respectively, to implement multi-level cell (MLC) in DC sweep mode. Based on neural activity, a neuromorphic system is performed by electrical stimulation. Accordingly, the pulse responses achieve longer endurance cycling (>10,000 cycles), MLC (potentiation and depression), spike-timing dependent plasticity (STDP), and excitatory postsynaptic current (EPSC) to mimic synapse using TiN/CeOx/Pt RRAM devices. Full article
(This article belongs to the Special Issue Memristive Materials and Devices)
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8 pages, 3666 KiB  
Article
Bipolar Switching Characteristics of Transparent WOX-Based RRAM for Synaptic Application and Neuromorphic Engineering
by Jihyung Kim, Jongmin Park and Sungjun Kim
Materials 2022, 15(20), 7185; https://doi.org/10.3390/ma15207185 - 15 Oct 2022
Cited by 7 | Viewed by 1881
Abstract
In this work, we evaluate the resistive switching (RS) and synaptic characteristics of a fully transparent resistive random-access memory (T-RRAM) device based on indium-tin-oxide (ITO) electrodes. Here, we fabricated ITO/WOX/ITO capacitor structure and incorporated DC-sputtered WOX as the switching layer [...] Read more.
In this work, we evaluate the resistive switching (RS) and synaptic characteristics of a fully transparent resistive random-access memory (T-RRAM) device based on indium-tin-oxide (ITO) electrodes. Here, we fabricated ITO/WOX/ITO capacitor structure and incorporated DC-sputtered WOX as the switching layer between the two ITO electrodes. The device shows approximately 77% (including the glass substrate) of optical transmittance in visible light and exhibits reliable bipolar switching behavior. The current-voltage (I–V) curve is divided into two types: partial and full curves affected by the magnitude of the positive voltage during the reset process. In the partial curve, we confirmed that the retention could be maintained for more than 104 s and the endurance for more than 300 cycles could be stably secured. The switching mechanism based on the formation/rupture of the filament is further explained through the extra oxygen vacancies provided by the ITO electrodes. Finally, we examined the responsive potentiation and depression to check the synaptic characteristics of the device. We believe that the transparent WOX-based RRAM could be a milestone for neuromorphic devices as well as future non-volatile transparent memory. Full article
(This article belongs to the Special Issue Memristive Materials and Devices)
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