J. Semicond. > 2021, Volume 42 > Issue 1 > Article Number: 014101

Study of short-term synaptic plasticity in Ion-Gel gated graphene electric-double-layer synaptic transistors

Chenrong Gong , Lin Chen , Weihua Liu and Guohe Zhang ,

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  • Corresponding author: Guohe Zhang, zhangguohe@xjtu.edu.cn
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    Abstract: Multi-terminal electric-double-layer transistors have recently attracted extensive interest in terms of mimicking synaptic and neural functions. In this work, an Ion-Gel gated graphene synaptic transistor was proposed to mimic the essential synaptic behaviors by exploiting the bipolar property of graphene and the ionic conductivity of Ion-Gel. The Ion-Gel dielectrics were deposited onto the graphene film by the spin coating process. We consider the top gate and graphene channel as a presynaptic and postsynaptic terminal, respectively. Basic synaptic functions were successfully mimicked, including the excitatory postsynaptic current (EPSC), the effect of spike amplitude and duration on EPSC, and paired-pulse facilitation (PPF). This work may facilitate the application of graphene synaptic transistors in flexible electronics.

    Key words: Ion-Gelgraphenesynaptic transistorsshort-term plasticity (STP)



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    Atluri P P, Regehr W G. Determinants of the time course of facilitation at the granule cell to purkinje cell synapse. J Neurosci, 1996, 16(18), 5661

    [1]

    von Neumann J. First draft of a report on the EDVAC. IEEE Ann Hist Comput, 1993, 15(4), 27

    [2]

    Nawrocki R A, Voyles R M, Shaheen S E. A mini review of neuromorphic architectures and implementations. IEEE Trans Electron Devices, 2016, 63(10), 3819

    [3]

    Kendall J D, Kumar S. The building blocks of a brain-inspired computer. Appl Phys Rev, 2020, 7(1), 11305

    [4]

    Yao P, Wu H, Gao B, et al. Fully hardware-implemented memristor convolutional neural network. Nature, 2020, 577(7792), 641

    [5]

    Roy K, Jaiswal A, Panda P. Towards spike-based machine intelligence with neuromorphic computing. Nature, 2019, 575(7784), 607

    [6]

    Pei J, Deng L, Song S, et al. Towards artificial general intelligence with hybrid Tianjic chip architecture. Nature, 2019, 572(7767), 106

    [7]

    Tian H, Mi W, Zhao H, et al. A novel artificial synapse with dual modes using bilayer graphene as the bottom electrode. Nanoscale, 2017, 9(27), 9275

    [8]

    Kandel E, Schwartz J, Jessell T, et al. Principles of neural science. New York: McGraw-Hill, 2013

    [9]

    Li J, Yang Y, Yin M, et al. Electrochemical and thermodynamic processes of metal nanoclusters enabled biorealistic synapses and leaky-integrate-and-fire neurons. Mater Horiz, 2020, 7(1), 71

    [10]

    Yan X, Zhao Q, Chen A P, et al. Vacancy-induced synaptic behavior in 2D WS2 nanosheet-based memristor for low-power neuromorphic computing. Small, 2019, 15(24), 1901423

    [11]

    Ielmini D, Wong H S P. In-memory computing with resistive switching devices. Nat Electron, 2018, 1(6), 333

    [12]

    Wang Z, Joshi S, Savel'ev S E, et al. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. Nat Mater, 2017, 16(1), 101

    [13]

    Liu B, Liu Z, Chiu I, et al. Programmable synaptic metaplasticity and below femtojoule spiking energy realized in graphene-based neuromorphic memristor. Acs Appl Mater Interfaces, 2018, 10(24), 20237

    [14]

    Yao Y, Huang X, Peng S, et al. Reconfigurable artificial synapses between excitatory and inhibitory modes based on single-gate graphene transistors. Adv Electron Mater, 2019, 5(5), 1800887

    [15]

    Huang H Y, Ge C, Zhang Q H, et al. Electrolyte-gated synaptic transistor with oxygen ions. Adv Funct Mater, 2019, 29(29), 1902702

    [16]

    Dai S, Zhao Y, Wang Y, et al. Recent advances in transistor-based artificial synapses. Adv Funct Mater, 2019, 29(42), 1903700

    [17]

    Liu M, Huang G, Feng P, et al. Artificial neuron synapse transistor based on silicon nanomembrane on plastic substrate. J Semicond, 2017, 38(6), 64006

    [18]

    Perea G, Navarrete M, Araque A. Tripartite synapses: Astrocytes process and control synaptic information. Trends Neurosci, 2009, 32(8), 421

    [19]

    Valtcheva S, Venance L. Astrocytes gate Hebbian synaptic plasticity in the striatum. Nat Commun, 2016, 7(1), 13845

    [20]

    He Y, Wan Q. Multi-terminal oxide-based electric-double-layer thin-film transistors for neuromorphic systems. ECS Trans, 2018, 86(11), 177

    [21]

    Singh M, Manoli K, Tiwari A, et al. The double layer capacitance of ionic liquids for electrolyte gating of ZnO thin film transistors and effect of gate electrodes. J Mater Chem C, 2017, 5(14), 3509

    [22]

    Schmidt E, Shi S, Ruden P P, et al. Characterization of the electric double layer formation dynamics of a metal/ionic liquid/metal structure. Acs Appl Mater Interfaces, 2016, 8(23), 14879

    [23]

    He Y, Yang Y, Nie S, et al. Electric-double-layer transistors for synaptic devices and neuromorphic systems. J Mater Chem C, 2018, 6(2), 5336

    [24]

    Kong L, Sun J, Qian C, et al. Ion-gel gated field-effect transistors with solution-processed oxide semiconductors for bioinspired artificial synapses. Org Electron, 2016, 39, 64

    [25]

    Wan X, Yang Y, Feng P, et al. Short-term plasticity and synaptic filtering emulated in electrolyte-gated IGZO transistors. IEEE Electron Device Lett, 2016, 37(3), 299

    [26]

    Jiang J, Hu W, Xie D, et al. 2D electric-double-layer phototransistor for photoelectronic and spatiotemporal hybrid neuromorphic integration. Nanoscale, 2019, 11(3), 1360

    [27]

    Cho J H, Lee J, Xia Y, et al. Printable ion-gel gate dielectrics for low-voltage polymer thin-film transistors on plastic. Nat Mater, 2008, 7(11), 900

    [28]

    Liu J, Qian Q, Zou Y, et al. Enhanced performance of graphene transistor with ion-gel top gate. Carbon, 2014, 68, 480

    [29]

    Kim B J, Jang H, Lee S, et al. High-performance flexible graphene field effect transistors with ion gel gate dielectrics. Nano Lett, 2010, 10(9), 3464

    [30]

    Chen L, Gong C, Zhang G, et al. Graphene synaptic transistor based on Ion-Gel dielectric. IEEE International Conference on Electron Devices and Solid-State Circuits, 2019, 1

    [31]

    Rs Z, Wg R. Short-term synaptic plasticity. Annu Rev Physiol, 2002, 64, 355

    [32]

    Abbott L F, Regehr W G. Synaptic computation. Nature, 2004, 431(7010), 796

    [33]

    Abraham W C. Metaplasticity: tuning synapses and networks for plasticity. Nat Rev Neurosci, 2008, 9(5), 387

    [34]

    Jiang J, Guo J, Wan X, et al. 2D MoS2 neuromorphic devices for brain-like computational systems. Small, 2017, 13(29), 1700933

    [35]

    Tian H, Mi W, Wang X, et al. Graphene dynamic synapse with modulatable plasticity. Nano Lett, 2015, 15(12), 8013

    [36]

    Wang H, Wu Y, Cong C, et al. Hysteresis of electronic transport in graphene transistors. Acs Nano, 2010, 4(12), 7221

    [37]

    Atluri P P, Regehr W G. Determinants of the time course of facilitation at the granule cell to purkinje cell synapse. J Neurosci, 1996, 16(18), 5661

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    C R Gong, L Chen, W H Liu, G H Zhang, Study of short-term synaptic plasticity in Ion-Gel gated graphene electric-double-layer synaptic transistors[J]. J. Semicond., 2021, 42(1): 014101. doi: 10.1088/1674-4926/42/1/014101.

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    History

    Manuscript received: 29 May 2020 Manuscript revised: 03 September 2020 Online: Accepted Manuscript: 03 November 2020 Uncorrected proof: 08 January 2021 Published: 09 January 2021

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