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Artificial synapse network on inorganic proton conductor for neuromorphic systems

Author

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  • Li Qiang Zhu

    (Jiangsu Provincial Key Laboratory of Photonic and Electronic Materials, School of Electronic Science & Engineering, Nanjing University
    Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences)

  • Chang Jin Wan

    (Jiangsu Provincial Key Laboratory of Photonic and Electronic Materials, School of Electronic Science & Engineering, Nanjing University
    Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences)

  • Li Qiang Guo

    (Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences)

  • Yi Shi

    (Jiangsu Provincial Key Laboratory of Photonic and Electronic Materials, School of Electronic Science & Engineering, Nanjing University)

  • Qing Wan

    (Jiangsu Provincial Key Laboratory of Photonic and Electronic Materials, School of Electronic Science & Engineering, Nanjing University
    Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences)

Abstract

The basic units in our brain are neurons, and each neuron has more than 1,000 synapse connections. Synapse is the basic structure for information transfer in an ever-changing manner, and short-term plasticity allows synapses to perform critical computational functions in neural circuits. Therefore, the major challenge for the hardware implementation of neuromorphic computation is to develop artificial synapse network. Here in-plane lateral-coupled oxide-based artificial synapse network coupled by proton neurotransmitters are self-assembled on glass substrates at room-temperature. A strong lateral modulation is observed due to the proton-related electrical-double-layer effect. Short-term plasticity behaviours, including paired-pulse facilitation, dynamic filtering and spatiotemporally correlated signal processing are mimicked. Such laterally coupled oxide-based protonic/electronic hybrid artificial synapse network proposed here is interesting for building future neuromorphic systems.

Suggested Citation

  • Li Qiang Zhu & Chang Jin Wan & Li Qiang Guo & Yi Shi & Qing Wan, 2014. "Artificial synapse network on inorganic proton conductor for neuromorphic systems," Nature Communications, Nature, vol. 5(1), pages 1-7, May.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4158
    DOI: 10.1038/ncomms4158
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    Cited by:

    1. S. Huang & E. Griffin & J. Cai & B. Xin & J. Tong & Y. Fu & V. Kravets & F. M. Peeters & M. Lozada-Hidalgo, 2023. "Gate-controlled suppression of light-driven proton transport through graphene electrodes," Nature Communications, Nature, vol. 14(1), pages 1-7, December.

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