A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse

Yiming Liu; Mingxuan Zhang; Yizhang Xia; Yinchao Zhao; Qifeng Lu

doi:10.1007/978-3-031-70684-4_9

A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse

Yiming Liu
, Mingxuan Zhang
, Yizhang Xia
, Yinchao Zhao
, Qifeng Lu^*

^*Corresponding author for this work

Xi'an Jiaotong-Liverpool University

Xi'an Jiaotong-Liverpool University
XiangTan University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

With the advent of the Big Data era, there is a growing demand for artificial intelligence, the Internet of Things, and machine learning. However, traditional computers based on von Neumann architecture face a significant challenge in the processing of vast amounts of data due to the separation of memory and the central processing unit. The hardware-based neuromorphic computing, which is inspired by the human brain, has the potential to significantly reduce energy consumption and realize a wide range of applications. Although a great achievement has been obtained, the uniformity in the electrical characteristics is still a challenge. Therefore, we designed and fabricated a memristor using ZnO nanowires (NWs) to achieve consistent modulation of conductive filaments. This memristor can emulate various synaptic functions, including paired-pulse facilitation, and short-term and long-term plasticity. As a proof of concept, the convolutional neural network simulation for MNIST recognition with 98.87% accuracy was achieved by the ZnO NWs-based memristors.

Original language	English
Title of host publication	Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications
Editors	Anwar P.P. Abdul Majeed, Eng Hwa Yap, Pengcheng Liu, Xiaowei Huang, Anh Nguyen, Wei Chen, Ue-Hwan Kim
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	108-115
Number of pages	8
ISBN (Print)	9783031706837
DOIs	https://doi.org/10.1007/978-3-031-70684-4_9
Publication status	Published - 2024
Event	11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023 - Taicang, China Duration: 6 Dec 2023 → 8 Dec 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1132 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023
Country/Territory	China
City	Taicang
Period	6/12/23 → 8/12/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

conductive filaments mechanism
convolutional neural networks
memristor
neuromorphic computing
ZnO nanowires

Access to Document

10.1007/978-3-031-70684-4_9

Cite this

Liu, Y., Zhang, M., Xia, Y., Zhao, Y., & Lu, Q. (2024). A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse. In A. P. P. Abdul Majeed, E. H. Yap, P. Liu, X. Huang, A. Nguyen, W. Chen, & U.-H. Kim (Eds.), Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications (pp. 108-115). (Lecture Notes in Networks and Systems; Vol. 1132 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-70684-4_9

Liu, Yiming ; Zhang, Mingxuan ; Xia, Yizhang et al. / A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse. Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications. editor / Anwar P.P. Abdul Majeed ; Eng Hwa Yap ; Pengcheng Liu ; Xiaowei Huang ; Anh Nguyen ; Wei Chen ; Ue-Hwan Kim. Springer Science and Business Media Deutschland GmbH, 2024. pp. 108-115 (Lecture Notes in Networks and Systems).

@inproceedings{9d467f54353e480d9fc54e9ded33818c,

title = "A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse",

abstract = "With the advent of the Big Data era, there is a growing demand for artificial intelligence, the Internet of Things, and machine learning. However, traditional computers based on von Neumann architecture face a significant challenge in the processing of vast amounts of data due to the separation of memory and the central processing unit. The hardware-based neuromorphic computing, which is inspired by the human brain, has the potential to significantly reduce energy consumption and realize a wide range of applications. Although a great achievement has been obtained, the uniformity in the electrical characteristics is still a challenge. Therefore, we designed and fabricated a memristor using ZnO nanowires (NWs) to achieve consistent modulation of conductive filaments. This memristor can emulate various synaptic functions, including paired-pulse facilitation, and short-term and long-term plasticity. As a proof of concept, the convolutional neural network simulation for MNIST recognition with 98.87\% accuracy was achieved by the ZnO NWs-based memristors.",

keywords = "conductive filaments mechanism, convolutional neural networks, memristor, neuromorphic computing, ZnO nanowires",

author = "Yiming Liu and Mingxuan Zhang and Yizhang Xia and Yinchao Zhao and Qifeng Lu",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023 ; Conference date: 06-12-2023 Through 08-12-2023",

year = "2024",

doi = "10.1007/978-3-031-70684-4\_9",

language = "English",

isbn = "9783031706837",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "108--115",

editor = "\{Abdul Majeed\}, \{Anwar P.P.\} and Yap, \{Eng Hwa\} and Pengcheng Liu and Xiaowei Huang and Anh Nguyen and Wei Chen and Ue-Hwan Kim",

booktitle = "Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications",

}

Liu, Y, Zhang, M, Xia, Y, Zhao, Y & Lu, Q 2024, A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse. in APP Abdul Majeed, EH Yap, P Liu, X Huang, A Nguyen, W Chen & U-H Kim (eds), Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications. Lecture Notes in Networks and Systems, vol. 1132 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 108-115, 11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023, Taicang, China, 6/12/23. https://doi.org/10.1007/978-3-031-70684-4_9

A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse. / Liu, Yiming; Zhang, Mingxuan; Xia, Yizhang et al.
Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications. ed. / Anwar P.P. Abdul Majeed; Eng Hwa Yap; Pengcheng Liu; Xiaowei Huang; Anh Nguyen; Wei Chen; Ue-Hwan Kim. Springer Science and Business Media Deutschland GmbH, 2024. p. 108-115 (Lecture Notes in Networks and Systems; Vol. 1132 LNNS).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse

AU - Liu, Yiming

AU - Zhang, Mingxuan

AU - Xia, Yizhang

AU - Zhao, Yinchao

AU - Lu, Qifeng

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024

Y1 - 2024

N2 - With the advent of the Big Data era, there is a growing demand for artificial intelligence, the Internet of Things, and machine learning. However, traditional computers based on von Neumann architecture face a significant challenge in the processing of vast amounts of data due to the separation of memory and the central processing unit. The hardware-based neuromorphic computing, which is inspired by the human brain, has the potential to significantly reduce energy consumption and realize a wide range of applications. Although a great achievement has been obtained, the uniformity in the electrical characteristics is still a challenge. Therefore, we designed and fabricated a memristor using ZnO nanowires (NWs) to achieve consistent modulation of conductive filaments. This memristor can emulate various synaptic functions, including paired-pulse facilitation, and short-term and long-term plasticity. As a proof of concept, the convolutional neural network simulation for MNIST recognition with 98.87% accuracy was achieved by the ZnO NWs-based memristors.

AB - With the advent of the Big Data era, there is a growing demand for artificial intelligence, the Internet of Things, and machine learning. However, traditional computers based on von Neumann architecture face a significant challenge in the processing of vast amounts of data due to the separation of memory and the central processing unit. The hardware-based neuromorphic computing, which is inspired by the human brain, has the potential to significantly reduce energy consumption and realize a wide range of applications. Although a great achievement has been obtained, the uniformity in the electrical characteristics is still a challenge. Therefore, we designed and fabricated a memristor using ZnO nanowires (NWs) to achieve consistent modulation of conductive filaments. This memristor can emulate various synaptic functions, including paired-pulse facilitation, and short-term and long-term plasticity. As a proof of concept, the convolutional neural network simulation for MNIST recognition with 98.87% accuracy was achieved by the ZnO NWs-based memristors.

KW - conductive filaments mechanism

KW - convolutional neural networks

KW - memristor

KW - neuromorphic computing

KW - ZnO nanowires

UR - https://www.scopus.com/pages/publications/85210841943

U2 - 10.1007/978-3-031-70684-4_9

DO - 10.1007/978-3-031-70684-4_9

M3 - Conference Proceeding

AN - SCOPUS:85210841943

SN - 9783031706837

T3 - Lecture Notes in Networks and Systems

SP - 108

EP - 115

BT - Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications

A2 - Abdul Majeed, Anwar P.P.

A2 - Yap, Eng Hwa

A2 - Liu, Pengcheng

A2 - Huang, Xiaowei

A2 - Nguyen, Anh

A2 - Chen, Wei

A2 - Kim, Ue-Hwan

PB - Springer Science and Business Media Deutschland GmbH

T2 - 11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023

Y2 - 6 December 2023 through 8 December 2023

ER -

Liu Y, Zhang M, Xia Y, Zhao Y, Lu Q. A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse. In Abdul Majeed APP, Yap EH, Liu P, Huang X, Nguyen A, Chen W, Kim UH, editors, Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications. Springer Science and Business Media Deutschland GmbH. 2024. p. 108-115. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-70684-4_9

A ZnO Nanowire Based Memristive Device and Its Application in Artificial Synapse

Abstract

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UN SDGs

Keywords

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