Reconfigurable Ion-Migration Driven Memristor for Multistate Neuromorphic Associative Learning

doi:10.1021/acsphotonics.5c00023

	Reconfigurable Ion-Migration Driven Memristor for Multistate Neuromorphic Associative Learning
	Yang, Jiaji1,2,3 ; Li, Xin1,2,3 ; Gu, Junzhe 1,3; Yu, Feilong 1; Chen, Jin 1; Liu, Juntong 1,3; Song, Yuxin 1,3; Lin, Xianjie 1,3; Chen, Xiaoshuang1,2,3,4,5 ; Lu, Wei1,2,3,4,5 ; Li, Guanhai 1,3,4,5
	2025-03-01
发表期刊	ACS PHOTONICS (IF:6.5[JCR-2023],6.6[5-Year])
ISSN	2330-4022
DOI	10.1021/acsphotonics.5c00023
摘要	The development of adaptive, multistate neuromorphic and photonic-memristive devices is essential for advancing intelligent systems capable of complex learning and decision-making. However, conventional devices face limitations in achieving simultaneous, tunable electrical and optical responses required for such biomimetic functions, often necessitating complex circuitry or material-specific modifications that hinder scalability and integration. Here, we present a reconfigurable, ion-migration driven WSe2-based memristor that addresses these challenges by enabling multistate, reversible switching between photoconductive and photovoltaic states. First-principles calculations were employed to investigate the Pd migration mechanism, revealing how controlled Pd ion movement dynamically modulates the device's band structure and contributes to its multistate functionality. Ultimately, the device achieves notable rectification ratios-up to 3 orders of magnitude-and a photovoltage modulation range of approximately +/- 0.5 V. These capabilities allow the device to emulate associative learning and multicondition decision-making in response to both external stimuli and internal states, directly supporting neuromorphic applications. These advancements, combined with an integration-friendly fabrication process, underscore the device's potential for secure communication, adaptive signal processing, and scalable neuromorphic systems.
关键词	neuromorphic computing photonic-memristive device ion migration bandgap modulation associativelearning
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收录类别	SCI ; EI
语种	英语
资助项目	National Key Research and Development Program of China[2023YFA1406900] ; Strategic Priority Research Program (B) of Chinese Academy of Sciences["XDB0580000","GJ0090406"] ; National Natural Science Foundation of China["62222514","62350073","U2341226","61991440","12227901","U23A6002"] ; Shanghai Science and Technology Committee["23ZR1482000","22JC1402900"] ; Natural Science Foundation of Zhejiang Province[LR22F050004] ; Shanghai Municipal Science and Technology Major Project[2019SHZDZX01] ; Youth Innovation Promotion Association[Y2021070] ; International Partnership Program of Chinese Academy of Sciences[112GJHZ2022002FN]
WOS研究方向	Science & Technology - Other Topics ; Materials Science ; Optics ; Physics
WOS类目	Nanoscience & Nanotechnology ; Materials Science, Multidisciplinary ; Optics ; Physics, Applied ; Physics, Condensed Matter
WOS记录号	WOS:001436092400001
出版者	AMER CHEMICAL SOC
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/493633
专题	物质科学与技术学院物质科学与技术学院_特聘教授组_陈效双组物质科学与技术学院_特聘教授组_陆卫组物质科学与技术学院_硕士生物质科学与技术学院_博士生
通讯作者	Chen, Xiaoshuang; Li, Guanhai
作者单位	1.Chinese Acad Sci, Shanghai Inst Tech Phys, State Key Lab Infrared Phys, 500 Yu Tian Rd, Shanghai 200083, Peoples R China 2.ShanghaiTech Univ, Sch Phys Sci & Technol, Shanghai 201210, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Univ Chinese Acad Sci, Hangzhou Inst Adv Study, Hangzhou 310024, Peoples R China 5.Shanghai Res Ctr Quantum Sci, Shanghai 201315, Peoples R China
第一作者单位	物质科学与技术学院
通讯作者单位	物质科学与技术学院
推荐引用方式 GB/T 7714	Yang, Jiaji,Li, Xin,Gu, Junzhe,et al. Reconfigurable Ion-Migration Driven Memristor for Multistate Neuromorphic Associative Learning[J]. ACS PHOTONICS,2025.
APA	Yang, Jiaji.,Li, Xin.,Gu, Junzhe.,Yu, Feilong.,Chen, Jin.,...&Li, Guanhai.(2025).Reconfigurable Ion-Migration Driven Memristor for Multistate Neuromorphic Associative Learning.ACS PHOTONICS.
MLA	Yang, Jiaji,et al."Reconfigurable Ion-Migration Driven Memristor for Multistate Neuromorphic Associative Learning".ACS PHOTONICS (2025).