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Nanomaterials
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Advances in Memristive Nanomaterials
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Advances in Memristive Nanomaterials

A special issue of Nanomaterials (ISSN 2079-4991). This special issue belongs to the section "Nanocomposite Materials".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 9278

Special Issue Editor

Prof. Dr. Zhongqiang Wang

E-Mail Website
Guest Editor
Key Laboratory for UV Light-Emitting Materials and Technology, Northeast Normal University, Changchun, China
Interests: memristive materials and neuromorphic devices

Special Issue Information

Dear Colleagues,

In the era of big data and the Internet of Things, a vast ocean of information needs to be processed in parallel with high energy efficiency. Brain-like neuromorphic systems that can process multiple types of data simultaneously could provide fundamental innovations for the traditional von-Neumann computer architecture. Memristive materials and devices are among the best hardware units for building neuromorphic systems due to the functional resemblance they bear to their biological counterparts (e.g., synapses and neurons), their inherent low voltage, their cost-effective fabrication, and their multi-bit storage capacity, meaning they have attracted considerable attention and have become a research hotspot.

Over the past decade, many great efforts have been devoted to the development of memristive materials for brain-like neuromorphic systems. However, there are still extensive fundamental research questions about memristive materials, such as behavior, function and performance. Therefore, the study of memristive physics, materials, and devices is still necessary. Apart from their neuromorphic computing applications, memristive materials can also be used in the fields of photodetection, sensor, or even security. This Research Topic aims to contribute a comprehensive overview of the recent important findings and progress, summarize current challenges, and hopefully propose perspectives for future research in memristive materials. This Research Topic will focus on the deployment of various memristive materials at the nanoscale and the related nanodevices for memory and neuromorphic applications.

Prof. Dr. Zhongqiang Wang
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. Nanomaterials 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 2900 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

  • memristive materials
  • neuromorphic applications
  • resistive switching
  • metal oxide
  • two-dimensional materials
  • artificial synapse
  • artificial neuron

Published Papers (6 papers)

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Research

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13 pages, 3297 KiB  
Article
SnO2-Based Memory Device with Filamentary Switching Mechanism for Advanced Data Storage and Computing
by Muhammad Ismail, Chandreswar Mahata, Myounggon Kang and Sungjun Kim
Nanomaterials 2023, 13(18), 2603; https://doi.org/10.3390/nano13182603 - 21 Sep 2023
Viewed by 974
Abstract
In this study, we fabricate a Pt/TiN/SnOx/Pt memory device using reactive sputtering to explore its potential for neuromorphic computing. The TiON interface layer, formed when TiN comes into contact with SnO2, acts as an oxygen vacancy reservoir, aiding the [...] Read more.
In this study, we fabricate a Pt/TiN/SnOx/Pt memory device using reactive sputtering to explore its potential for neuromorphic computing. The TiON interface layer, formed when TiN comes into contact with SnO2, acts as an oxygen vacancy reservoir, aiding the creation of conductive filaments in the switching layer. Our SnOx-based device exhibits remarkable endurance, with over 200 DC cycles, ON/FFO ratio (>20), and 104 s retention. Set and reset voltage variabilities are impressively low, at 9.89% and 3.2%, respectively. Controlled negative reset voltage and compliance current yield reliable multilevel resistance states, mimicking synaptic behaviors. The memory device faithfully emulates key neuromorphic characteristics, encompassing both long-term potentiation (LTP) and long-term depression (LTD). The filamentary switching mechanism in the SnOx-based memory device is explained by an oxygen vacancy concentration gradient, where current transport shifts from Ohmic to Schottky emission dominance across different resistance states. These findings exemplify the potential of SnOx-based devices for high-density data storage memory and revolutionary neuromorphic computing applications. Full article
(This article belongs to the Special Issue Advances in Memristive Nanomaterials)
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11 pages, 2396 KiB  
Article
Polyacrylonitrile Passivation for Enhancing the Optoelectronic Switching Performance of Halide Perovskite Memristor for Image Boolean Logic Applications
by Xiaohan Zhang, Xiaoning Zhao and Zhongqiang Wang
Nanomaterials 2023, 13(15), 2174; https://doi.org/10.3390/nano13152174 - 26 Jul 2023
Cited by 3 | Viewed by 1059
Abstract
For the CH3NH3PbI3-based optoelectronic memristor, the high ion-migration randomness induces high fluctuation in the resistive switching (RS) parameters. Grain boundaries (GBs) are well known as the ion-migration sites due to their low energy barrier. Herein, a polyacrylonitrile [...] Read more.
For the CH3NH3PbI3-based optoelectronic memristor, the high ion-migration randomness induces high fluctuation in the resistive switching (RS) parameters. Grain boundaries (GBs) are well known as the ion-migration sites due to their low energy barrier. Herein, a polyacrylonitrile (PAN) passivation method is developed to reduce GBs of the CH3NH3PbI3 film and improve the switching uniformity of the memristor. The crystal grain size of CH3NH3PbI3 increases with the addition of PAN, and the corresponding number of GBs is consequently reduced. The fluctuations of the RS parameters of the memristor device are significantly reduced. With the memristor, nonvolatile image sensing, image memory, and image Boolean operations are demonstrated. This work proposes a strategy for developing high-performance CH3NH3PbI3 optoelectronic memristors. Full article
(This article belongs to the Special Issue Advances in Memristive Nanomaterials)
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13 pages, 5150 KiB  
Article
Electrical Characteristics of CMOS-Compatible SiOx-Based Resistive-Switching Devices
by Maria N. Koryazhkina, Dmitry O. Filatov, Stanislav V. Tikhov, Alexey I. Belov, Dmitry A. Serov, Ruslan N. Kryukov, Sergey Yu. Zubkov, Vladislav A. Vorontsov, Dmitry A. Pavlov, Evgeny G. Gryaznov, Elena S. Orlova, Sergey A. Shchanikov, Alexey N. Mikhaylov and Sungjun Kim
Nanomaterials 2023, 13(14), 2082; https://doi.org/10.3390/nano13142082 - 16 Jul 2023
Cited by 2 | Viewed by 851
Abstract
The electrical characteristics and resistive switching properties of memristive devices have been studied in a wide temperature range. The insulator and electrode materials of these devices (silicon oxide and titanium nitride, respectively) are fully compatible with conventional complementary metal-oxide-semiconductor (CMOS) fabrication processes. Silicon [...] Read more.
The electrical characteristics and resistive switching properties of memristive devices have been studied in a wide temperature range. The insulator and electrode materials of these devices (silicon oxide and titanium nitride, respectively) are fully compatible with conventional complementary metal-oxide-semiconductor (CMOS) fabrication processes. Silicon oxide is also obtained through the low-temperature chemical vapor deposition method. It is revealed that the as-fabricated devices do not require electroforming but their resistance state cannot be stored before thermal treatment. After the thermal treatment, the devices exhibit bipolar-type resistive switching with synaptic behavior. The conduction mechanisms in the device stack are associated with the effect of traps in the insulator, which form filaments in the places where the electric field is concentrated. The filaments shortcut the capacitance of the stack to different degrees in the high-resistance state (HRS) and in the low-resistance state (LRS). As a result, the electron transport possesses an activation nature with relatively low values of activation energy in an HRS. On the contrary, Ohm’s law and tunneling are observed in an LRS. CMOS-compatible materials and low-temperature fabrication techniques enable the easy integration of the studied resistive-switching devices with traditional analog–digital circuits to implement new-generation hardware neuromorphic systems. Full article
(This article belongs to the Special Issue Advances in Memristive Nanomaterials)
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12 pages, 3512 KiB  
Article
Approaches for Memristive Structures Using Scratching Probe Nanolithography: Towards Neuromorphic Applications
by Roman V. Tominov, Zakhar E. Vakulov, Vadim I. Avilov, Ivan A. Shikhovtsov, Vadim I. Varganov, Victor B. Kazantsev, Lovi Raj Gupta, Chander Prakash and Vladimir A. Smirnov
Nanomaterials 2023, 13(10), 1583; https://doi.org/10.3390/nano13101583 - 9 May 2023
Viewed by 1386
Abstract
This paper proposes two different approaches to studying resistive switching of oxide thin films using scratching probe nanolithography of atomic force microscopy (AFM). These approaches allow us to assess the effects of memristor size and top-contact thickness on resistive switching. For that purpose, [...] Read more.
This paper proposes two different approaches to studying resistive switching of oxide thin films using scratching probe nanolithography of atomic force microscopy (AFM). These approaches allow us to assess the effects of memristor size and top-contact thickness on resistive switching. For that purpose, we investigated scratching probe nanolithography regimes using the Taguchi method, which is known as a reliable method for improving the reliability of the result. The AFM parameters, including normal load, scratch distance, probe speed, and probe direction, are optimized on the photoresist thin film by the Taguchi method. As a result, the pinholes with diameter ranged from 25.4 ± 2.2 nm to 85.1 ± 6.3 nm, and the groove array with a depth of 40.5 ± 3.7 nm and a roughness at the bottom of less than a few nanometers was formed. Then, based on the Si/TiN/ZnO/photoresist structures, we fabricated and investigated memristors with different spot sizes and TiN top contact thickness. As a result, the HRS/LRS ratio, USET, and ILRS are well controlled for a memristor size from 27 nm to 83 nm and ranged from ~8 to ~128, from 1.4 ± 0.1 V to 1.8 ± 0.2 V, and from (1.7 ± 0.2) × 10−10 A to (4.2 ± 0.6) × 10−9 A, respectively. Furthermore, the HRS/LRS ratio and USET are well controlled at a TiN top contact thickness from 8.3 ± 1.1 nm to 32.4 ± 4.2 nm and ranged from ~22 to ~188 and from 1.15 ± 0.05 V to 1.62 ± 0.06 V, respectively. The results can be used in the engineering and manufacturing of memristive structures for neuromorphic applications of brain-inspired artificial intelligence systems. Full article
(This article belongs to the Special Issue Advances in Memristive Nanomaterials)
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8 pages, 2190 KiB  
Communication
Digital and Analog Resistive Switching Behavior in Si-NCs Embedded in a Si/SiO2 Multilayer Structure for Neuromorphic Systems
by Alfredo Morales-Sánchez, Karla Esther González-Flores, Sergio Alfonso Pérez-García, Sergio González-Torres, Blas Garrido-Fernández, Luis Hernández-Martínez and Mario Moreno-Moreno
Nanomaterials 2023, 13(6), 986; https://doi.org/10.3390/nano13060986 - 9 Mar 2023
Cited by 1 | Viewed by 1755
Abstract
In this work, we report the digital and analog resistive-switching (RS) characteristics in a memristor based on silicon nanocrystals (Si-NCs) integrated into a complementary metal-oxide-semiconductor (MOS) structure. Si-NCs with a diameter of 5.48 ± 1.24 nm embedded in a SiO2/Si-NCs/SiO2 [...] Read more.
In this work, we report the digital and analog resistive-switching (RS) characteristics in a memristor based on silicon nanocrystals (Si-NCs) integrated into a complementary metal-oxide-semiconductor (MOS) structure. Si-NCs with a diameter of 5.48 ± 1.24 nm embedded in a SiO2/Si-NCs/SiO2 multilayer structure acts as an RS layer. These devices exhibit bipolar RS with an intermediate resistance step during SET and RESET processes, which is believed to lie in the Si-NCs layer acting as charge-trapping nodes. The endurance studies of about 70 DC cycles indicate an ON/OFF ratio of ~106 and a retention time larger than 104 s. Long-term potentiation (LTP, −2 V) and long-term depression (LTD, +4 V) are obtained by applying consecutive identical pulse voltages of 150 ms duration. The current value gradually increases/decreases (LTP/LTD) as the pulse number increases. Three consecutive identical pulses of −2 V/150 ms (LTP) separated by 5 and 15 min show that the last current value obtained at the end of each pulse train is kept, confirming an analog RS behavior. These characteristics provide a possible way to mimic biological synapse functions for applications in neuromorphic computing in Si-NCs-based CMOS structures. Full article
(This article belongs to the Special Issue Advances in Memristive Nanomaterials)
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Review

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45 pages, 16512 KiB  
Review
Review of Electrochemically Synthesized Resistive Switching Devices: Memory Storage, Neuromorphic Computing, and Sensing Applications
by Somnath S. Kundale, Girish U. Kamble, Pradnya P. Patil, Snehal L. Patil, Kasturi A. Rokade, Atul C. Khot, Kiran A. Nirmal, Rajanish K. Kamat, Kyeong Heon Kim, Ho-Myoung An, Tukaram D. Dongale and Tae Geun Kim
Nanomaterials 2023, 13(12), 1879; https://doi.org/10.3390/nano13121879 - 17 Jun 2023
Cited by 10 | Viewed by 2781
Abstract
Resistive-switching-based memory devices meet most of the requirements for use in next-generation information and communication technology applications, including standalone memory devices, neuromorphic hardware, and embedded sensing devices with on-chip storage, due to their low cost, excellent memory retention, compatibility with 3D integration, in-memory [...] Read more.
Resistive-switching-based memory devices meet most of the requirements for use in next-generation information and communication technology applications, including standalone memory devices, neuromorphic hardware, and embedded sensing devices with on-chip storage, due to their low cost, excellent memory retention, compatibility with 3D integration, in-memory computing capabilities, and ease of fabrication. Electrochemical synthesis is the most widespread technique for the fabrication of state-of-the-art memory devices. The present review article summarizes the electrochemical approaches that have been proposed for the fabrication of switching, memristor, and memristive devices for memory storage, neuromorphic computing, and sensing applications, highlighting their various advantages and performance metrics. We also present the challenges and future research directions for this field in the concluding section. Full article
(This article belongs to the Special Issue Advances in Memristive Nanomaterials)
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