J. Semicond. > 2021, Volume 42 > Issue 1 > Article Number: 014102

Voltage-dependent plasticity and image Boolean operations realized in a WO x-based memristive synapse

Jiajuan Shi , Ya Lin , , Tao Zeng , Zhongqiang Wang , , Xiaoning Zhao , Haiyang Xu and Yichun Liu

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  • Corresponding author: Ya Lin, Email: liny474@nenu.edu.cn; Zhongqiang Wang, wangzq752@nenu.edu.cn
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    Abstract: The development of electronic devices that possess the functionality of biological synapses is a crucial step towards neuromorphic computing. In this work, we present a WOx-based memristive device that can emulate voltage-dependent synaptic plasticity. By adjusting the amplitude of the applied voltage, we were able to reproduce short-term plasticity (STP) and the transition from STP to long-term potentiation. The stimulation with high intensity induced long-term enhancement of conductance without any decay process, thus representing a permanent memory behavior. Moreover, the image Boolean operations (including intersection, subtraction, and union) were also demonstrated in the memristive synapse array based on the above voltage-dependent plasticity. The experimental achievements of this study provide a new insight into the successful mimicry of essential characteristics of synaptic behaviors.

    Key words: memristorartificial synapseshort-term plasticitylong-term potentiationimage Boolean operations



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    Satoh T, Chiyokura H. Boolean operations on sets using surface data. Proceedings of the First ACM Symposium on Solid Modeling Foundations and CAD/CAM Applications, 1991, 119

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    Mäntylä M. Boolean operations of 2-manifolds through vertex neighborhood classification. ACM Trans Graph, 1986, 5(1), 1

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    Gardan Y, Perrin E. An algorithm reducing 3D Boolean operations to a 2D problem: concepts and results. Comput Aid Des, 1996, 28(4), 277

    [1]

    Zidan M A, Strachan J P, Lu W D. The future of electronics based on memristive systems. Nat Electron, 2018, 1(1), 22

    [2]

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

    [3]

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

    [4]

    Wang Z Q, Xu H Y, Li X H, et al. Synaptic learning and memory functions achieved using oxygen ion migration/diffusion in an amorphous InGaZnO memristor. Adv Funct Mater, 2012, 22(13), 2759

    [5]

    Yan X B, Zhao J H, Liu S, et al. Memristor with Ag-cluster-doped TiO2 films as artificial synapse for neuroinspired computing. Adv Funct Mater, 2018, 28(1), 1705320

    [6]

    Wang J R, Zhuge F. Memristive synapses for brain-inspired computing. Adv Mater Technol, 2019, 4(3), 1800544

    [7]

    Ohno T, Hasegawa T, Tsuruoka T, et al. Short-term plasticity and long-term potentiation mimicked in single inorganic synapses. Nat Mater, 2011, 10(8), 591

    [8]

    Kim S, Du C, Sheridan P, et al. Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity. Nano Lett, 2015, 15(3), 2203

    [9]

    Jo S H, Chang T, Ebong I, et al. Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett, 2010, 10(4), 1297

    [10]

    Li Y, Zhong Y, Zhang J, et al. Activity-dependent synaptic plasticity of a chalcogenide electronic synapse for neuromorphic systems. Sci Rep, 2015, 4(1), 4906

    [11]

    Serrano-Gotarredona T, Masquelier T, Prodromakis T, et al. STDP and STDP variations with memristors for spiking neuromorphic learning systems. Front Neurosci, 2013, 7(2), 2

    [12]

    Zucker R S, Regehr W G. Short-term synaptic plasticity. Annu Rev Physiol, 2002, 64(1), 355

    [13]

    Debanne D, Gähwiler, B H, Thompson S M. Heterogeneity of synaptic plasticity at unitary CA3–CA1 and CA3–CA3 connections in rat hippocampal slice cultures. J Neurosci, 1999, 19(24), 10664

    [14]

    Kim M K, Lee J S. Short-term plasticity and long-term potentiation in artificial biosynapses with diffusive dynamics. ACS Nano, 2018, 12(2), 1680

    [15]

    Wang Z, Zeng T, Ren Y et al. Toward a generalized Bienenstock-Cooper-Munro rule for spatiotemporal learning via triplet-STDP in memristive devices. Nat Commun, 2020, 11(1), 1510

    [16]

    Abraham W C, Gustafsson B, Wigström H. Single high strength afferent volleys can produce long-term potentiation in the hippocampus in vitro. Neurosci Lett, 1986, 70(2), 217

    [17]

    Yang J T, Ge C, Du J Y, et al. Artificial synapses emulated by an electrolyte-gated tungsten-oxide transistor. Adv Mater, 2018, 30(34), 1801548

    [18]

    Du J Y, Ge C, Riahi H, et al. Dual-gated MoS2 transistors for synaptic and programmable logic functions. Adv Electron Mater, 2020, 6(5), 1901408

    [19]

    Lin Y, Zeng T, Xu H Y, et al. Transferable and flexible artificial memristive synapse based on WOx Schottky junction on arbitrary substrates. Adv Electron Mater, 2018, 4(12), 1800373

    [20]

    Lin Y, Wang C, Ren Y, et al. Analog –digital hybrid memristive devices for image pattern recognition with tunable learning accuracy and speed. Small Methods, 2019, 3(10), 1900160

    [21]

    Kamiya R, Zucher R S. Residual Ca2 + and short-term synaptic plasticity. Nature, 1994, 371, 603

    [22]

    Wang T Y, Meng J L, He Z Y, et al. Room-temperature developed flexible biomemristor with ultralow switching voltage for array learning. Nanoscale, 2020, 12(16), 9116

    [23]

    Waser R, Aono M. Nanoionics-based resistive switching memories. Nanosci Technol, 2009, 158

    [24]

    Wang W, Xu J, Ma H, et al. Insertion of nanoscale AgInSbTe Layer between the Ag electrode and the CH3NH3PbI3 electrolyte layer enabling enhanced multilevel memory. ACS Appl Nano Mater, 2019, 2(1), 307

    [25]

    Atkinson R C, Shiffrin R M. Human memory: A proposed system and its control processes. Psychol Learn Motiv, 1968, 2, 89

    [26]

    Harary F, Wilcox G W. Boolean operations on graphs. Math Scand, 1967, 20(1), 41

    [27]

    Satoh T, Chiyokura H. Boolean operations on sets using surface data. Proceedings of the First ACM Symposium on Solid Modeling Foundations and CAD/CAM Applications, 1991, 119

    [28]

    Mäntylä M. Boolean operations of 2-manifolds through vertex neighborhood classification. ACM Trans Graph, 1986, 5(1), 1

    [29]

    Gardan Y, Perrin E. An algorithm reducing 3D Boolean operations to a 2D problem: concepts and results. Comput Aid Des, 1996, 28(4), 277

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    J J Shi, Y Lin, T Zeng, Z Q Wang, X N Zhao, H Y Xu, Y C Liu, Voltage-dependent plasticity and image Boolean operations realized in a WO x-based memristive synapse[J]. J. Semicond., 2021, 42(1): 014102. doi: 10.1088/1674-4926/42/1/014102.

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    History

    Manuscript received: 21 May 2020 Manuscript revised: 06 June 2020 Online: Accepted Manuscript: 04 September 2020 Uncorrected proof: 08 January 2021 Published: 09 January 2021

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