Journal of Inorganic Materials, Volume. 38, Issue 4, 413(2023)

Intrinsically Stretchable Threshold Switching Memristor for Artificial Neuron Implementations

Yu TIAN1,2, Xiaojian ZHU2、*, Cui SUN2, Xiaoyu YE2, Huiyuan LIU2, and Runwei LI2
Author Affiliations
  • 11. School of Materials Science and Chemical Engineering, Ningbo University, Ningbo 315211, China
  • 22. Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China
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    References(32)

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    [8] YANG J Q, WANG R, WANG Z P et al. Leaky integrate-and-fire neurons based on perovskite memristor for spiking neural networks[J]. Nano Energy, 74: 104828(2020).

    [13] ZHU J X, ZHANG X, WANG M R et al. Flexible memristive spiking neuron for neuromorphic sensing and computing[J]. Acta Physica Sinica, 338(2022).

    [16] TANG D X, LIU J Y, WANG Y X et al. Research progress in flexible resistive random access memory materials[J]. J, 81(2020).

    [19] ZHAN S Y, WANG Q G, WANG X L et al[conf-proc].

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    [25] YANG J, CAO J, HAN J et al. Stretchable multifunctional self-powered systems with Cu-EGaIn liquid metal electrodes[J]. Nano Energy, 101: 107582(2022).

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    Yu TIAN, Xiaojian ZHU, Cui SUN, Xiaoyu YE, Huiyuan LIU, Runwei LI. Intrinsically Stretchable Threshold Switching Memristor for Artificial Neuron Implementations[J]. Journal of Inorganic Materials, 2023, 38(4): 413

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    Paper Information

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    Received: Nov. 28, 2022

    Accepted: --

    Published Online: Oct. 17, 2023

    The Author Email: Xiaojian ZHU (zhuxj@nimte.ac.cn)

    DOI:10.15541/jim20220712

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