Phase-Transition-Induced VO2 Thin Film IR Photodetector and Threshold Switching Selector for Optical Neural Network Applications

doi:10.1002/aelm.202001254

HFCAS OpenIR

	Phase-Transition-Induced VO2 Thin Film IR Photodetector and Threshold Switching Selector for Optical Neural Network Applications
	Zhou, Xi 1,2,3; Zhao, Liang 4,5; Zhen, Weili 6; Lin, Yinyue 1,2,3; Wang, Chunlin 1,2,3; Pan, Tianyu 1,2,3; Li, Le 1,2,3; Du, Guanlin 1,2,3; Lu, Linfeng 1,2,3; Cao, Xun 7; Li, Dongdong 1,2,3
	2021-03-30
发表期刊	ADVANCED ELECTRONIC MATERIALS
ISSN	2199-160X
通讯作者	Zhao, Liang(leonzhao@reliancememory.com) ; Li, Dongdong(lidd@sari.ac.cn)
摘要	As the architecture of choice for future artificial-intelligent systems, the ideas of in-memory- and in-sensor-computing paradigms based on non-von-Neumann architecture possess broad application prospects such as neuromorphic and sensor-memory-processor fusion systems. At the same time, these promising applications put diversified and strict requirements on the device performances, such as fast response to external signals, robust data security, and 3D integration potential. In this work, Au@VO2 IR photodetectors and Ti/Au/VO2/Ti/Au threshold switching selectors are constructed, where the VO2 thin films are realized by magnetron sputtering and water-vapor assisted post-annealing. Fast IR response is achieved in Au@VO2 photodetectors through a surface plasmon resonance-assisted metal-insulator transition. Furthermore, electroforming-free, tunable threshold voltage, steep switching slope, and selectivity of more than two orders of magnitude are observed in Ti/Au/VO2/Ti/Au threshold switching selector. Combining the functionalities of photodetection and selector, a VO2-based optical convolution engine demonstrates accurate and secure image-processing capability. These VO2-based devices are demonstrated as promising candidates for novel non-volatile memory, neuromorphic computing and sensor-memory-processor fusion applications.
关键词	neuromorphic computing optical neural networks photodetectors threshold switching vanadium dioxide
DOI	10.1002/aelm.202001254
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61622407] ; Natural Science Foundation of Shanghai[19ZR1479100] ; Shanxi Science and Technology Department[20201101012]
项目资助者	National Natural Science Foundation of China ; Natural Science Foundation of Shanghai ; Shanxi Science and Technology Department
WOS研究方向	Science & Technology - Other Topics ; Materials Science ; Physics
WOS类目	Nanoscience & Nanotechnology ; Materials Science, Multidisciplinary ; Physics, Applied
WOS记录号	WOS:000634682300001
出版者	WILEY
引用统计	被引频次：28[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.hfcas.ac.cn:8080/handle/334002/121356
专题	中国科学院合肥物质科学研究院
通讯作者	Zhao, Liang; Li, Dongdong
作者单位	1.Chinese Acad Sci, Shanghai Adv Res Inst, CAS Key Lab Low Carbon Convers Sci & Engn, 99 Haike Rd,Zhangjiang Hitech Pk, Shanghai 201210, Peoples R China 2.Chinese Acad Sci, Shanghai Adv Res Inst, Interdisciplinary Res, 99 Haike Rd,Zhangjiang Hitech Pk, Shanghai 201210, Peoples R China 3.Univ Chinese Acad Sci, Sch Microelect, 19 Yuquan Rd, Beijing 100049, Peoples R China 4.Hefei Reliance Memory Ltd, Bldg F4-11F,Innovat Ind Pk Phase 2, Hefei 230088, Peoples R China 5.Zhejiang Univ, Coll Informat Sci & Elect Engn, 38 Zheda Rd, Hangzhou 310007, Peoples R China 6.Chinese Acad Sci, High Magnet Field Lab, Hefei 230031, Peoples R China 7.Chinese Acad Sci, Shanghai Inst Ceram, State Key Lab High Performance Ceram & Superfine, Shanghai 200050, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Xi,Zhao, Liang,Zhen, Weili,et al. Phase-Transition-Induced VO2 Thin Film IR Photodetector and Threshold Switching Selector for Optical Neural Network Applications[J]. ADVANCED ELECTRONIC MATERIALS,2021.
APA	Zhou, Xi.,Zhao, Liang.,Zhen, Weili.,Lin, Yinyue.,Wang, Chunlin.,...&Li, Dongdong.(2021).Phase-Transition-Induced VO2 Thin Film IR Photodetector and Threshold Switching Selector for Optical Neural Network Applications.ADVANCED ELECTRONIC MATERIALS.
MLA	Zhou, Xi,et al."Phase-Transition-Induced VO2 Thin Film IR Photodetector and Threshold Switching Selector for Optical Neural Network Applications".ADVANCED ELECTRONIC MATERIALS (2021).