Switching mechanism for TiO2 memristor and quantitative analysis of exponential model parameters

doi:10.1088/1674-1056/24/8/088401

中国物理B ›› 2015, Vol. 24 ›› Issue (8): 88401-088401.doi: 10.1088/1674-1056/24/8/088401

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇下一篇

Switching mechanism for TiO₂ memristor and quantitative analysis of exponential model parameters

王小平^{a b}, 陈敏^{a b}, 沈轶^{a b}

a School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;
b Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan 430074, China

收稿日期:2014-11-17 修回日期:2015-03-02 出版日期:2015-08-05 发布日期:2015-08-05
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos. 61374150 and 61374171), the State Key Program of the National Natural Science Foundation of China (Grant No. 61134012), the National Basic Research Program of China (Grant No. 2011CB710606), and the Fundamental Research Funds for the Central Universities, China (Grant No. 2013TS126).

Switching mechanism for TiO₂ memristor and quantitative analysis of exponential model parameters

Wang Xiao-Ping (王小平)^{a b}, Chen Min (陈敏)^{a b}, Shen Yi (沈轶)^{a b}

a School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;
b Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan 430074, China

Received:2014-11-17 Revised:2015-03-02 Online:2015-08-05 Published:2015-08-05
Contact: Wang Xiao-Ping E-mail:wangxiaoping@hust.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos. 61374150 and 61374171), the State Key Program of the National Natural Science Foundation of China (Grant No. 61134012), the National Basic Research Program of China (Grant No. 2011CB710606), and the Fundamental Research Funds for the Central Universities, China (Grant No. 2013TS126).

摘要/Abstract

摘要：

The memristor, as the fourth basic circuit element, has drawn worldwide attention since its physical implementation was released by HP Labs in 2008. However, at the nano-scale, there are many difficulties for memristor physical realization. So a better understanding and analysis of a good model will help us to study the characteristics of a memristor. In this paper, we analyze a possible mechanism for the switching behavior of a memristor with a Pt/TiO₂/Pt structure, and explain the changes of electronic barrier at the interface of Pt/TiO₂. Then, a quantitative analysis about each parameter in the exponential model of memristor is conducted based on the calculation results. The analysis results are validated by simulation results. The efforts made in this paper will provide researchers with theoretical guidance on choosing appropriate values for (α, β, χ, γ) in this exponential model.

关键词: memristor, switching behavior, electronic barrier, exponential model

Abstract:

Key words: memristor, switching behavior, electronic barrier, exponential model

中图分类号: (Passive circuit components)

84.32.-y

85.35.-p (Nanoelectronic devices) 03.65.-w (Quantum mechanics)

王小平, 陈敏, 沈轶. Switching mechanism for TiO₂ memristor and quantitative analysis of exponential model parameters[J]. 中国物理B, 2015, 24(8): 88401-088401.

Wang Xiao-Ping (王小平), Chen Min (陈敏), Shen Yi (沈轶). Switching mechanism for TiO₂ memristor and quantitative analysis of exponential model parameters[J]. Chin. Phys. B, 2015, 24(8): 88401-088401.

参考文献 33

[1]	Chua L O 1971 IEEE Trans. Circuit Theory 18 507
[2]	Chua L O and Kang S M 1976 Proc. IEEE 64 209
[3]	Strukov D B, Snider G S, Stewart G R and Williams R S 2008 Nature 453 80
[4]	Adhikari S P, Sah M P, Kim H and Chua L O 2013 IEEE Trans. Circ. Syst. I 60 3008
[5]	Chua L O 2012 Proc. IEEE 100 1920
[6]	Merrikh-Bayat F and Shouraki S B 2013 IEEE Trans. Cybern. 43 269
[7]	Zhou J and Huang D 2012 Chin. Phys. B 21 048401
[8]	Tian X B, Xu H and Li Q J 2013 Chin. Phys. B 22 088502
[9]	Tian X B and Xu H 2014 Chin. Phys. B 23 068401
[10]	Bao B C, Hu F W, Liu Z and Xu J P 2014 Chin. Phys. B 23 070503
[11]	Biolek Z, Biolek D and Biokova V 2009 Radioengineering 18 211
[12]	Joglekar Y N and Wolf S J 2009 Eur. J. Phys. 30 661
[13]	Benderli S 2009 Electron. Lett. 45 377
[14]	Strukov D B and Williams R S 2009 Appl. Phys. 94 515
[15]	Yakopcic C, Taha T M, Subramanyam G, Pino R E and Rogers S 2011 IEEE Electron Dev. Lett. 32 1436
[16]	Pino R E, Bohl J W, McDonald N, Wysocki B, Rozwood P, Campbell K A, Oblea A and Timisina A 2010 Proc. IEEE/ACM Int. Symp. Nanoscale Archit., June 17–18, 2010, Anaheim, CA, USA, p. 1
[17]	Abdalla H and Pickett M D 2011 IEEE Int. Symp. Circ. Syst., May 15–18, 2011, Rio de Janeiro, p. 1832
[18]	Laiho M, Lehtonen E, Russell A and Dudek P 2010 Neuromorphic Eng. 10 24
[19]	Wu G Y and Wu K P 1992 J. Appl. Phys. 71 1259
[20]	Lehtonen E and Laiho M 2010 12th International Workshop on Cellular Nanoscale Networks and Their Applications, February 3–5, 2010, Berkeley, CA, USA, p. 1
[21]	Chang T, Jo S H, Kim K H, Sheridan P, Gaba S and Lu W 2012 Appl. Phys. 102 857
[22]	Zhu X, Tang Y H, Wu C Q, Wu J J and Yi X 2014 Chin. Phys. B 23 028501
[23]	Simmons J G 1963 J. Appl. Phys. 34 1793
[24]	Xu K D, Zhang Y H, Wang L, Yuan M Q, Joines W T and Liu Q H 2013 Proc. SPIE 8911 89110H
[25]	Wang X Y, Andrew L F, Herbert H C I, Victor S and Qi W G 2012 Chin. Phys. B 21 108501
[26]	Wu H G, Bao B C and Chen M 2014 Chin. Phys. B 23 118401
[27]	Yang J J, Pickett M D, Li X, Ohlberg D A, Stewart D R and Williams R S 2008 Nat. Nanotechnol. 3 429
[28]	Kwon D H, Kim K M, Jang J H, Jeon J M, Lee M H, Kim G H, Li X S, Park G S, Lee B, Han S W, Kim M Y and Hwang C S 2010 Nat. Nanotechnol. 5 148
[29]	John B 1947 Phys. Rev. 71 717
[30]	Doghish M Y and Ho F D 1992 IEEE Trans. Electron Dev. 39 2771
[31]	Charlesby A 1953 Proc. Phys. Soc. B 66 533
[32]	Sze S M and Ng K K 2007 Physics of Semiconductor Devices (New Jersey: John Wiley & Sons Inc.) pp. 134–187
[33]	Ohdomari I and Tu K N 1980 J. Appl. Phys. 51 3735

Switching mechanism for TiO₂ memristor and quantitative analysis of exponential model parameters

Switching mechanism for TiO₂ memristor and quantitative analysis of exponential model parameters

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

参考文献 33

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	Zhan-Hong Guo(郭展宏), Zhi-Jun Li(李志军), Meng-Jiao Wang(王梦蛟), and Ming-Lin Ma(马铭磷). Hopf bifurcation and phase synchronization in memristor-coupled Hindmarsh-Rose and FitzHugh-Nagumo neurons with two time delays[J]. 中国物理B, 2023, 32(3): 38701-038701.
[2]	Fan Sun(孙帆), Jing Su(粟静), Jie Li(李杰), Shukai Duan(段书凯), and Xiaofang Hu(胡小方). Memristor's characteristics: From non-ideal to ideal[J]. 中国物理B, 2023, 32(2): 28401-028401.
[3]	Xiao-Juan Lian(连晓娟), Jin-Ke Fu(付金科), Zhi-Xuan Gao(高志瑄),Shi-Pu Gu(顾世浦), and Lei Wang(王磊). High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristors[J]. 中国物理B, 2023, 32(1): 17304-017304.
[4]	Zhi-Jun Li(李志军), Wen-Qiang Xie(谢文强), Jin-Fang Zeng(曾金芳), and Yi-Cheng Zeng(曾以成). Firing activities in a fractional-order Hindmarsh-Rose neuron with multistable memristor as autapse[J]. 中国物理B, 2023, 32(1): 10503-010503.
[5]	Xiaodong Jiao(焦晓东), Mingfeng Yuan(袁明峰), Jin Tao(陶金), Hao Sun(孙昊), Qinglin Sun(孙青林), and Zengqiang Chen(陈增强). Memristor hyperchaos in a generalized Kolmogorov-type system with extreme multistability[J]. 中国物理B, 2023, 32(1): 10507-010507.
[6]	Xi Zhu(朱熙), Hui Xu(徐晖), Weiping Yang(杨为平), Zhiwei Li(李智炜), Haijun Liu(刘海军), Sen Liu(刘森), Yinan Wang(王义楠), and Hongchang Long(龙泓昌). High throughput N-modular redundancy for error correction design of memristive stateful logic[J]. 中国物理B, 2023, 32(1): 18502-018502.
[7]	Sheng-Hao Jia(贾生浩), Yu-Xia Li(李玉霞), Qing-Yu Shi(石擎宇), and Xia Huang(黄霞). Design and FPGA implementation of a memristor-based multi-scroll hyperchaotic system[J]. 中国物理B, 2022, 31(7): 70505-070505.
[8]	Qi Qin(秦琦), Miaocheng Zhang(张缪城), Suhao Yao(姚苏昊), Xingyu Chen(陈星宇), Aoze Han(韩翱泽),Ziyang Chen(陈子洋), Chenxi Ma(马晨曦), Min Wang(王敏), Xintong Chen(陈昕彤), Yu Wang(王宇),Qiangqiang Zhang(张强强), Xiaoyan Liu(刘晓燕), Ertao Hu(胡二涛), Lei Wang(王磊), and Yi Tong(童祎). Fabrication and investigation of ferroelectric memristors with various synaptic plasticities[J]. 中国物理B, 2022, 31(7): 78502-078502.
[9]	Ming-Jian Guo(郭明健), Shu-Kai Duan(段书凯), and Li-Dan Wang(王丽丹). Pulse coding off-chip learning algorithm for memristive artificial neural network[J]. 中国物理B, 2022, 31(7): 78702-078702.
[10]	Yan-Mei Lu(卢艳梅), Chun-Hua Wang(王春华), Quan-Li Deng(邓全利), and Cong Xu(徐聪). The dynamics of a memristor-based Rulkov neuron with fractional-order difference[J]. 中国物理B, 2022, 31(6): 60502-060502.
[11]	Wu-Yang Zhu(朱伍洋), Yi-Fei Pu(蒲亦非), Bo Liu(刘博), Bo Yu(余波), and Ji-Liu Zhou(周激流). A mathematical analysis: From memristor to fracmemristor[J]. 中国物理B, 2022, 31(6): 60204-060204.
[12]	Wenwu Jiang(蒋文武), Jie Li(李杰), Hongbo Liu(刘洪波), Xicong Qian(钱曦聪), Yuan Ge(葛源), Lidan Wang(王丽丹), and Shukai Duan(段书凯). Memristor-based multi-synaptic spiking neuron circuit for spiking neural network[J]. 中国物理B, 2022, 31(4): 40702-040702.
[13]	Ai-Xue Qi(齐爱学), Bin-Da Zhu(朱斌达), and Guang-Yi Wang(王光义). Complex dynamic behaviors in hyperbolic-type memristor-based cellular neural network[J]. 中国物理B, 2022, 31(2): 20502-020502.
[14]	Qiankun Sun(孙乾坤), Shaobo He(贺少波), Kehui Sun(孙克辉), and Huihai Wang(王会海). A novel hyperchaotic map with sine chaotification and discrete memristor[J]. 中国物理B, 2022, 31(12): 120501-120501.
[15]	Yuan Ge(葛源), Jie Li(李杰), Wenwu Jiang(蒋文武), Lidan Wang(王丽丹), and Shukai Duan(段书凯). A spintronic memristive circuit on the optimized RBF-MLP neural network[J]. 中国物理B, 2022, 31(11): 110702-110702.