|
|
Electronic synapses based on ultrathin quasi-two-dimensional gallium oxide memristor |
Shuopei Wang(王硕培)1,2, Congli He(何聪丽)1,3, Jian Tang(汤建)1,2, Rong Yang(杨蓉)1,4, Dongxia Shi(时东霞)1,2,4, Guangyu Zhang(张广宇)1,2,4,5 |
1 CAS Key Laboratory of Nanoscale Physics and Devices;Beijing National Laboratory for Condensed Matter Physics and Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China;
2 School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100190, China;
3 Institute of Advanced Materials, Beijing Normal University, Beijing 100875, China;
4 Beijing Key Laboratory for Nanomaterials and Nanodevices, Beijing 100190, China;
5 Songshan Lake Materials Laboratory, Dongguan 523808, China |
|
|
Abstract Synapse emulation is very important for realizing neuromorphic computing, which could overcome the energy and throughput limitations of today's computing architectures. Memristors have been extensively studied for using in nonvolatile memory storage and neuromorphic computing. In this paper, we report the fabrication of vertical sandwiched memristor device using ultrathin quasi-two-dimensional gallium oxide produced by squeegee method. The as-fabricated two-terminal memristor device exhibited the essential functions of biological synapses, such as depression and potentiation of synaptic weight, transition from short time memory to long time memory, spike-timing-dependent plasticity, and spike-rate-dependent plasticity. The synaptic weight of the memristor could be tuned by the applied voltage pulse, number, width, and frequency. We believe that the injection of the top Ag cations should play a significant role for the memristor phenomenon. The ultrathin of medium layer represents an advance to integration in vertical direction for future applications and our results provide an alternative way to fabricate synaptic devices.
|
Received: 25 October 2018
Revised: 14 November 2018
Accepted manuscript online:
|
PACS:
|
73.50.-h
|
(Electronic transport phenomena in thin films)
|
|
68.65.-k
|
(Low-dimensional, mesoscopic, nanoscale and other related systems: structure and nonelectronic properties)
|
|
87.19.lv
|
(Learning and memory)
|
|
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 11834017), the Strategic Priority Research Program of Chinese Academy of Sciences (CAS) (Grant No. XDB30000000), the Key Research Program of Frontier Sciences of the CAS (Grant No. QYZDB-SSW-SLH004), the National Key R&D Program of China (Grant No. 2016YFA0300904), and the Fundamental Research Funds for the Central Universities, China (Grant No. 310421101). |
Corresponding Authors:
Congli He, Guangyu Zhang
E-mail: conglihe@bnu.edu.cn;gyzhang@iphy.ac.cn
|
Cite this article:
Shuopei Wang(王硕培), Congli He(何聪丽), Jian Tang(汤建), Rong Yang(杨蓉), Dongxia Shi(时东霞), Guangyu Zhang(张广宇) Electronic synapses based on ultrathin quasi-two-dimensional gallium oxide memristor 2019 Chin. Phys. B 28 017304
|
[1] |
Yegnanarayana B 2009 Artificial Neural Networks (PHI Learning Pvt. Ltd.)
|
[2] |
Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, Guez A, Hubert T, Baker L, Lai M and Bolton A 2017 Nature 550 354
|
[3] |
Ananthanarayanan R, Esser S K, Simon H D and Modha D S 2009 Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis p. 63
|
[4] |
Indiveri G, Chicca E and Douglas R 2006 IEEE Trans. Neural Netw. 17 211
|
[5] |
Izhikevich E M and Edelman G M 2008 Proc. Natl. Academy Sci. 105 3593
|
[6] |
Chua L 1971 IEEE Trans. Circuit Theory 18 507
|
[7] |
Lee M J, Lee C B, Lee D, Lee S R, Chang M, Hur J H, Kim Y B, Kim C J, Seo D H and Seo S 2011 Nat. Mater. 10 625
|
[8] |
Jo S H, Chang T, Ebong I, Bhadviya B B, Mazumder P and Lu W 2010 Nano Lett. 10 1297
|
[9] |
Strukov D B, Snider G S, Stewart D R and Williams R S 2008 Nature 453 80
|
[10] |
Ohno T, Hasegawa T, Tsuruoka T, Terabe K, Gimzewski J K and Aono M 2011 Nat. Mater. 10 591
|
[11] |
Guo D Y, Wu Z P, An Y H, Li P G, Wang P C, Chu X L, Guo X C, Zhi Y S, Lei M, Li L H and Tang W H 2015 Appl. Phys. Lett. 106 042105
|
[12] |
Guo D Y, Wu Z P, Zhang L J, Yang T, Hu Q R, Lei M, Li P G, Li L H and Tang W H 2015 Appl. Phys. Lett. 107 032104
|
[13] |
Aoki Y, Wiemann C, Feyer V, Kim H S, Schneider C M, Ill-Yoo H and Martin M 2014 Nat. Commun. 5 3473
|
[14] |
Hsu C W and Chou L J 2012 Nano Lett. 12 4247
|
[15] |
Gao X, Xia Y, Ji J, Xu H, Su Y, Li H, Yang C, Guo H, Yin J and Liu Z 2010 Appl. Phys. Lett. 97 193501
|
[16] |
Wang M, Cai S, Pan C, Wang C, Lian X, Zhuo Y, Xu K, Cao T, Pan X, Wang B, Liang S J, Yang J J, Wang P and Miao F 2018 Nat. Electron. 1 130
|
[17] |
Zhao H, Dong Z, Tian H, DiMarzi D, Han M G, Zhang L, Yan X, Liu F, Shen L, Han S J, Cronin S, Wu W, Tice J, Guo J and Wang H 2017 Advanced Mater. 29 1703232
|
[18] |
Sangwan V K, Lee H S, Bergeron H, Balla I, Beck M E, Chen K S and Hersam M C 2018 Nature 554 500
|
[19] |
Huh W, Jang S, Lee J Y, Lee D, Lee D, Lee J M, Park H G, Kim J C, Jeong H Y, Wang G and Lee C H 2018 Adv. Mater. 30 e1801447
|
[20] |
Yang C S, Shang D S, Liu N, Shi G, Shen X, Yu R C, Li Y Q and Sun Y 2017 Advanced Mater. 29 1700906
|
[21] |
Cabrera N and Mott N F 1949 Rep. Prog. Phys. 12 163
|
[22] |
Regan M J, Tostmann H, Pershan P S, Magnussen O M, DiMasi E, Ocko B M and Deutsch M 1997 Phys. Rev. B 55 10786
|
[23] |
Zavabeti A, Ou J Z, Carey B J, Syed N, Orrell-Trigg R, Mayes E L, Xu C, Kavehei O, O'mullane A P and Kaner R B 2017 Science 358 332
|
[24] |
Lawrenz F, Lange P, Severin N, Rabe J P, Helm C A and Block S 2015 Langmuir 31 5836
|
[25] |
Carey B J, Ou J Z, Clark R M, Berean K J, Zavabeti A, Chesman A S, Russo S P, Lau D W, Xu Z Q, Bao Q, Kevehei O, Gibson B C, Dickey M D, Kaner R B, Daeneke T and Kalantar-Zadeh K 2017 Nat. Commun. 8 14482
|
[26] |
Syed N, Zavabeti A, Ou J Z, Mohiuddin M, Pillai N, Carey B J, Zhang B Y, Datta R S, Jannat A, Haque F, Messalea K A, Xu C, Russo S P, McConville C F, Daeneke T and Kalantar-Zadeh K 2018 Nat. Commun. 9 3618
|
[27] |
Kim D, Thissen P, Viner G, Lee D W, Choi W, Chabal Y J and Lee J B 2013 ACS Appl. Mater. Interfaces 5 179
|
[28] |
Hattori Y, Taniguchi T, Watanabe K and Nagashio K 2015 ACS Nano 9 916
|
[29] |
Shi Y, Liang X, Yuan B, Chen V, Li H, Hui F, Yu Z, Yuan F, Pop E, Wong H S P and Lanza M 2018 Nat. Electron. 1 458
|
[30] |
Yang Y and Huang R 2018 Nat. Electron. 1 274
|
[31] |
Caporale N and Dan Y 2008 Annu. Rev. Neuroscience 31 25
|
[32] |
Wang Z, Joshi S, Savel'ev S E, Jiang H, Midya R, Lin P, Hu M, Ge N, Strachan J P and Li Z 2017 Nat. Mater. 16 101
|
[33] |
Chang T, Jo S H and Lu W 2011 ACS Nano 5 7669
|
[34] |
Kuzum D, Jeyasingh R G, Lee B and Wong H S P 2012 Nano Lett. 12 2179
|
[35] |
Bi G Q and Poo M M 1998 J. Neuroscience 18 10464
|
[36] |
Song S, Miller K D and Abbott L F 2000 Nat. Neuroscience 3 919
|
No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|