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Micromachines
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Amorphous Oxide Semiconductor-Based Memristive Devices and Thin-Film Transistors
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Amorphous Oxide Semiconductor-Based Memristive Devices and Thin-Film Transistors

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "E：Engineering and Technology".

Deadline for manuscript submissions: closed (5 February 2022) | Viewed by 8551

Special Issue Editors

Dr. Asal Kiazadeh

E-Mail Website
Guest Editor
Department of Materials Science, Faculty of Science and Technology, Universidade NOVA de Lis-boa and CEMOP/UNINOVA, Campus de Caparica, 2829-516 Caparica, Portugal
Interests: IoT-memristor; thin film transistor; oxide electronic; paper electronic
Special Issues, Collections and Topics in MDPI journals
Dr. Emanuel Carlos

E-Mail Website
Guest Editor
i3N/CENIMAT, Department of Materials Science, Faculty of Science and Technology, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal
Interests: solution-based (sol-gel and combustion) metal oxides thin films; high-κ dielectrics; thin film transistors; resistive switching devices; printed electronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

New materials and computational paradigms more efficient than traditional von Neumann architectures need to be pursued to develop new neuromorphic paradigms, capable of parallel computation with power consumption several orders of magnitude below that of the digital microprocessors currently in use. Memristors might be the enabler of this much-needed technological leap. However, memristor devices are not yet fully understood, nor is the modeling yet at the point needed for the design of productive integrated systems. The present solutions are not yet at a stage making large-scale integration possible, partly because memristors do not share building materials and processing steps with mainstream electronics.

The implementation of memristive devices based on amorphous oxide semiconductors (AOSs) and eventually integrated with thin-film transistors (TFTs), based on the same material/technique, for electronic support should significantly reduce manufacturing costs and efforts for system-on-panel and IoT applications. To surpass these challenges vast investment has been made on solution-based electronic devices to reduce the electronic waste and reach a more affordable technology to society.

We invite researchers and scientists to showcase their work in this Special Issue with research papers and review articles that focus on trends in AOS-based memristors, thin-film transistors, diodes and integration strategies, modelling, and simulation, from fundamental research to applications.

Dr. Asal Kiazadeh
Dr. Emanuel Carlos
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. Micromachines is an international peer-reviewed open access monthly 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

  • Solution-based technology (coating and printing techniques)
  • AOS memristive devices and systems
  • neuromorphic computing with AOS-based memristors
  • pattern recognition based on AOS memristors
  • integration of AOS memristors with TFTs
  • system-on-panel applications
  • novel circuits on AOS-based memristors
  • modeling and simulation of AOS processes for memristive devices
  • circuit models and simulation of AOS memristors and TFTs
  • resistive RAM based on AOS materials

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Published Papers (3 papers)

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Research

14 pages, 3861 KiB  
Article
Compact Model for Bipolar and Multilevel Resistive Switching in Metal-Oxide Memristors
by Eugeny Ryndin, Natalia Andreeva and Victor Luchinin
Micromachines 2022, 13(1), 98; https://doi.org/10.3390/mi13010098 - 8 Jan 2022
Cited by 7 | Viewed by 2695
Abstract
The article presents the results of the development and study of a combined circuitry (compact) model of thin metal oxide films based memristive elements, which makes it possible to simulate both bipolar switching processes and multilevel tuning of the memristor conductivity taking into [...] Read more.
The article presents the results of the development and study of a combined circuitry (compact) model of thin metal oxide films based memristive elements, which makes it possible to simulate both bipolar switching processes and multilevel tuning of the memristor conductivity taking into account the statistical variability of parameters for both device-to-device and cycle-to-cycle switching. The equivalent circuit of the memristive element and the equation system of the proposed model are considered. The software implementation of the model in the MATLAB has been made. The results of modeling static current-voltage characteristics and transient processes during bipolar switching and multilevel turning of the conductivity of memristive elements are obtained. A good agreement between the simulation results and the measured current-voltage characteristics of memristors based on TiOx films (30 nm) and bilayer TiO2/Al2O3 structures (60 nm/5 nm) is demonstrated. Full article
(This article belongs to the Special Issue Amorphous Oxide Semiconductor-Based Memristive Devices and Thin-Film Transistors)
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12 pages, 3576 KiB  
Article
Contact Engineering Approach to Improve the Linearity of Multilevel Memristive Devices
by Natalia Andreeva, Dmitriy Mazing, Alexander Romanov, Marina Gerasimova, Dmitriy Chigirev and Victor Luchinin
Micromachines 2021, 12(12), 1567; https://doi.org/10.3390/mi12121567 - 16 Dec 2021
Cited by 4 | Viewed by 2217
Abstract
Physical mechanisms underlying the multilevel resistive tuning over seven orders of magnitude in structures based on TiO2/Al2O3 bilayers, sandwiched between platinum electrodes, are responsible for the nonlinear dependence of the conductivity of intermediate resistance states on the writing [...] Read more.
Physical mechanisms underlying the multilevel resistive tuning over seven orders of magnitude in structures based on TiO2/Al2O3 bilayers, sandwiched between platinum electrodes, are responsible for the nonlinear dependence of the conductivity of intermediate resistance states on the writing voltage. To improve the linearity of the electric-field resistance tuning, we apply a contact engineering approach. For this purpose, platinum top electrodes were replaced with aluminum and copper ones to induce the oxygen-related electrochemical reactions at the interface with the Al2O3 switching layer of the structures. Based on experimental results, it was found that electrode material substitution provokes modification of the physical mechanism behind the resistive switching in TiO2/Al2O3 bilayers. In the case of aluminum electrodes, a memory window has been narrowed down to three orders of magnitude, while the linearity of resistance tuning was improved. For copper electrodes, a combination of effects related to metal ion diffusion with oxygen vacancies driven resistive switching was responsible for a rapid relaxation of intermediate resistance states in TiO2/Al2O3 bilayers. Full article
(This article belongs to the Special Issue Amorphous Oxide Semiconductor-Based Memristive Devices and Thin-Film Transistors)
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13 pages, 3427 KiB  
Article
A Neural Network Approach towards Generalized Resistive Switching Modelling
by Guilherme Carvalho, Maria Pereira, Asal Kiazadeh and Vítor Grade Tavares
Micromachines 2021, 12(9), 1132; https://doi.org/10.3390/mi12091132 - 21 Sep 2021
Cited by 1 | Viewed by 2237
Abstract
Resistive switching behaviour has been demonstrated to be a common characteristic to many materials. In this regard, research teams to date have produced a plethora of different devices exhibiting diverse behaviour, but when system design is considered, finding a ‘one-model-fits-all’ solution can be [...] Read more.
Resistive switching behaviour has been demonstrated to be a common characteristic to many materials. In this regard, research teams to date have produced a plethora of different devices exhibiting diverse behaviour, but when system design is considered, finding a ‘one-model-fits-all’ solution can be quite difficult, or even impossible. However, it is in the interest of the community to achieve more general modelling tools for design that allows a quick model update as devices evolve. Laying the grounds with such a principle, this paper presents an artificial neural network learning approach to resistive switching modelling. The efficacy of the method is demonstrated firstly with two simulated devices and secondly with a 4 μm2 amorphous IGZO device. For the amorphous IGZO device, a normalized root-mean-squared error (NRMSE) of 5.66 × 10−3 is achieved with a [2, 50,50 ,1] network structure, representing a good balance between model complexity and accuracy. A brief study on the number of hidden layers and neurons and its effect on network performance is also conducted with the best NRMSE reported at 4.63 × 10−3. The low error rate achieved in both simulated and real-world devices is a good indicator that the presented approach is flexible and can suit multiple device types. Full article
(This article belongs to the Special Issue Amorphous Oxide Semiconductor-Based Memristive Devices and Thin-Film Transistors)
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