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A review of memristor: material and structure design, device performance, applications and prospects
With the booming growth of artificial intelligence (AI), the traditional von Neumann computing architecture based on complementary metal oxide semiconductor devices are facing memory wall and power wall. Memristor based in-memory computing can potentially overcome the current bottleneck of computer...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980037/ https://www.ncbi.nlm.nih.gov/pubmed/36872944 http://dx.doi.org/10.1080/14686996.2022.2162323 |
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author | Xiao, Yongyue Jiang, Bei Zhang, Zihao Ke, Shanwu Jin, Yaoyao Wen, Xin Ye, Cong |
author_facet | Xiao, Yongyue Jiang, Bei Zhang, Zihao Ke, Shanwu Jin, Yaoyao Wen, Xin Ye, Cong |
author_sort | Xiao, Yongyue |
collection | PubMed |
description | With the booming growth of artificial intelligence (AI), the traditional von Neumann computing architecture based on complementary metal oxide semiconductor devices are facing memory wall and power wall. Memristor based in-memory computing can potentially overcome the current bottleneck of computer and achieve hardware breakthrough. In this review, the recent progress of memory devices in material and structure design, device performance and applications are summarized. Various resistive switching materials, including electrodes, binary oxides, perovskites, organics, and two-dimensional materials, are presented and their role in the memristor are discussed. Subsequently, the construction of shaped electrodes, the design of functional layer and other factors influencing the device performance are analyzed. We focus on the modulation of the resistances and the effective methods to enhance the performance. Furthermore, synaptic plasticity, optical-electrical properties, the fashionable applications in logic operation and analog calculation are introduced. Finally, some critical issues such as the resistive switching mechanism, multi-sensory fusion, system-level optimization are discussed. |
format | Online Article Text |
id | pubmed-9980037 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-99800372023-03-03 A review of memristor: material and structure design, device performance, applications and prospects Xiao, Yongyue Jiang, Bei Zhang, Zihao Ke, Shanwu Jin, Yaoyao Wen, Xin Ye, Cong Sci Technol Adv Mater Focus on Materials and Technologies for Memristors and Neuromorphic Devices With the booming growth of artificial intelligence (AI), the traditional von Neumann computing architecture based on complementary metal oxide semiconductor devices are facing memory wall and power wall. Memristor based in-memory computing can potentially overcome the current bottleneck of computer and achieve hardware breakthrough. In this review, the recent progress of memory devices in material and structure design, device performance and applications are summarized. Various resistive switching materials, including electrodes, binary oxides, perovskites, organics, and two-dimensional materials, are presented and their role in the memristor are discussed. Subsequently, the construction of shaped electrodes, the design of functional layer and other factors influencing the device performance are analyzed. We focus on the modulation of the resistances and the effective methods to enhance the performance. Furthermore, synaptic plasticity, optical-electrical properties, the fashionable applications in logic operation and analog calculation are introduced. Finally, some critical issues such as the resistive switching mechanism, multi-sensory fusion, system-level optimization are discussed. Taylor & Francis 2023-02-28 /pmc/articles/PMC9980037/ /pubmed/36872944 http://dx.doi.org/10.1080/14686996.2022.2162323 Text en © 2023 The Author(s). Published by National Institute for Materials Science in partnership with Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Focus on Materials and Technologies for Memristors and Neuromorphic Devices Xiao, Yongyue Jiang, Bei Zhang, Zihao Ke, Shanwu Jin, Yaoyao Wen, Xin Ye, Cong A review of memristor: material and structure design, device performance, applications and prospects |
title | A review of memristor: material and structure design, device performance, applications and prospects |
title_full | A review of memristor: material and structure design, device performance, applications and prospects |
title_fullStr | A review of memristor: material and structure design, device performance, applications and prospects |
title_full_unstemmed | A review of memristor: material and structure design, device performance, applications and prospects |
title_short | A review of memristor: material and structure design, device performance, applications and prospects |
title_sort | review of memristor: material and structure design, device performance, applications and prospects |
topic | Focus on Materials and Technologies for Memristors and Neuromorphic Devices |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980037/ https://www.ncbi.nlm.nih.gov/pubmed/36872944 http://dx.doi.org/10.1080/14686996.2022.2162323 |
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