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    Giant ferroelectric resistance switching controlled by a modulatory terminal for low-power neuromorphic in-memory computing

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    Type
    Article
    Authors
    Xue, Fei
    He, Xin cc
    Wang, Zhenyu
    Duran Retamal, Jose Ramon
    Chai, Zheng
    Jing, Lingling
    Zhang, Chenhui cc
    Fang, Hui
    Chai, Yang
    Jiang, Tao
    Zhang, Weidong
    Alshareef, Husam N. cc
    Ji, Zhigang
    Li, Lain-Jong cc
    He, Jr-Hau cc
    Zhang, Xixiang cc
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Electrical and Computer Engineering Program
    Functional Nanomaterials and Devices Research Group
    KAUST Solar Center (KSC)
    Material Science and Engineering Program
    Nano Energy Lab
    Physical Science and Engineering (PSE) Division
    KAUST Grant Number
    CRF-2015- 2634-CRG4
    CRF-2016-2996-CRG5
    Date
    2021-04-15
    Online Publication Date
    2021-04-15
    Print Publication Date
    2021-05
    Embargo End Date
    2022-03-02
    Permanent link to this record
    http://hdl.handle.net/10754/667793
    
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    Abstract
    Ferroelectrics have been demonstrated as excellent building blocks for high-performance non-volatile memories, including memristors, which play critical roles in the hardware implementation of artificial synapses and in-memory computing. Here, we report that the emerging van der Waals ferroelectric α-In2Se3 can be used to successfully implement heterosynaptic plasticity (a fundamental but rarely emulated synaptic form) and achieve a resistance-switching ratio of heterosynaptic memristors above 103, which is two order of magnitude larger than that in other similar devices. The polarization change of ferroelectric α-In2Se3 channel is responsible for the resistance switching at various paired terminals.The third terminal of α-In2Se3 memristors exhibits nonvolatile control over channel current at a picoampere level, endowing the devices with picojoule read-energy consumption to emulate the associative heterosynaptic learning. Our simulation proves that both supervised and unsupervised learning manners can be implemented in α-In2Se3 neutral networks with high image recognition accuracy. Moreover, these heterosynaptic devices can naturally realize Boolean logic without an additional circuit component. Our results suggest that van der Waals ferroelectrics hold great potential for applications in complex, energy-efficient, brain-inspired computing systems and logic-in-memory computers.
    Citation
    Xue, F., He, X., Wang, Z., Retamal, J. R. D., Chai, Z., Jing, L., … Zhang, X. (2021). Giant Ferroelectric Resistance Switching Controlled by a Modulatory Terminal for Low-Power Neuromorphic In-Memory Computing. Advanced Materials, 2008709. doi:10.1002/adma.202008709
    Sponsors
    The research presented here was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: CRF-2015- 2634-CRG4 and CRF-2016- 2996 -CRG5. Y. C. thanks the financial support from the Research Grant Council of Hong Kong (152053/18E). We thank Prof. Tuo-Hung Hou for helpful suggestions. J. -H. H. thanks the financial support from the startup fund of City University of Hong Kong.
    Publisher
    Wiley
    Journal
    Advanced Materials
    DOI
    10.1002/adma.202008709
    10.1002/adma.202170167
    ae974a485f413a2113503eed53cd6c53
    10.1002/adma.202008709
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Electrical and Computer Engineering Program; Material Science and Engineering Program; KAUST Solar Center (KSC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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