J. Semicond. > 2017, Volume 38 > Issue 6 > 064006
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SEMICONDUCTOR DEVICES

Artificial neuron synapse transistor based on silicon nanomembrane on plastic substrate

Minjie Liu1, Gaoshan Huang1, , Ping Feng2, , Qinglei Guo1, Feng Shao2, Ziao Tian1, Gongjin Li1, Qing Wan2 and Yongfeng Mei1

+ Author Affiliations

 Corresponding author: Gaoshan Huang Email:gshuang@fudan.edu.cn; Ping Feng Email:pfeng@nju.edu.cn

DOI: 10.1088/1674-4926/38/6/064006

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Abstract: Silicon nanomembrane (SiNM) transistors gated by chitosan membrane were fabricated on plastic substrate to mimic synapse behaviors. The device has both a bottom proton gate (BG) and multiple side gates (SG). Electrical transfer properties of BG show hysteresis curves different from those of typical SiO2 gate dielectric. Synaptic behaviors and functions by linear accumulation and release of protons have been mimicked on this device:excitatory post-synaptic current (EPSC) and paired pulse facilitation behavior of biological synapses were mimicked and the paired-pulse facilitation index could be effectively tuned by the spike interval applied on the BG. Synaptic behaviors and functions, including short-term memory and long-term memory, were also experimentally demonstrated in BG mode. Meanwhile, spiking logic operation and logic modulation were realized in SG mode.

Key words: silicon nanomembrane, chitosan membrane, excitatory post-synaptic current



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Fig. 1.  (Color online) (a) Schematic diagram of SiNM transistors gated by chitosan membrane at BG test mode. The balls represent holes in SiNM. (b) Optical microscope image of the devices. (c) Output curves with different BG voltages (VBG, step: 1 V). (d) Transfer curves IDS-VBG with different VDS.

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Fig. 2.  (a) EPSCs triggered by two successive presynaptic spikes when successive pulses of different interval times (10 and 100 ms) were applied on the BG with VDS= 2 V. Here we define the PPF index as ( $A_{1}-A_{0})$ / $A_{0}$ . (b) PPF index measured at different interval times. The red line is the linear fitting result.

DownLoad: Full-Size Img PowerPoint
Fig. 3.  (a) EPSC responses of device to the stimulus train with a 12 gate spikes (-2.0 V, 10 ms). The $V_{\mathrm{DS}}$ is fixed at 2.5 V. (b) The width of the presynapse spike on the gate electrode was changed from 10 to 80 ms.

DownLoad: Full-Size Img PowerPoint
Fig. 4.  (a) Schematic diagram of SiNM transistors gated by chitosan membrane at SG test mode. (b) Input-output characteristics of the OR pulse logic tuned by negative spikes applied on the controlled SGs. EPSC signal changes linearly by multiple SGs.

DownLoad: Full-Size Img PowerPoint
[1]
Neuron C D, Triller A. The dynamic synapse. Neuron, 2013, 80(3):691 doi: 10.1016/j.neuron.2013.10.013
[2]
Drachman D A. Do we have brain to spare. Neurology, 2005, 64(12):2004 doi: 10.1212/01.WNL.0000166914.38327.BB
[3]
Zucker R S, Regehr W G. Short-term synaptic plasticity. Rev Physiol, 2002, 64(1):355 doi: 10.1146/annurev.physiol.64.092501.114547
[4]
Bi G Q, Poo M M. Synaptic modifications in cultured hippocampal neurons:dependence on spike timing, synaptic strength, and postsynaptic cell type. J Neurosci, 1998, 18(24):10464 http://neurophysics.ustc.edu.cn/pdf/Bi98.pdf
[5]
Voglis G, Tavernarakis N. The role of synaptic ion channels in synaptic plasticity. Embo Rep, 2006, 7(11):1104 doi: 10.1038/sj.embor.7400830
[6]
Kuzum D, Jeyasingh R G, Lee B, et al. Nanoelectronic programmable synapses based on phase change materials for braininspired computing. Nano Lett, 2011, 12(5):2179 doi: 10.1021/nl201040y
[7]
Bielecki A, Kalita P, Lewandowski M, et al. Compartment model of neuropeptide synaptic transport with impulse control. Biol Cybern, 2008, 99(6):443 doi: 10.1007/s00422-008-0250-0
[8]
Merolla P A, Arthur J V, Alvarezicaza R, et al. Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface. Science, 2014, 345(6197):668 doi: 10.1126/science.1254642
[9]
Furber S B, Galluppi F, Temple S, et al. The SpiNNaker project. Proc IEEE, 2014, 102(5):652 doi: 10.1109/JPROC.2014.2304638
[10]
Ramakrishnan S, Hasler P E, Gordon C. Floating gate synapses with spike-time-dependent plasticity. IEEE Trans Biomed Circuits Syst, 2011, 5(3):244 doi: 10.1109/TBCAS.2011.2109000
[11]
Indiveri G, Chicca E, Douglas R. A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Trans Neural Network, 2006, 17(1):211 doi: 10.1109/TNN.2005.860850
[12]
Zhu L Q, Wan C J, Guo L Q, et al. Artificial synapse network on inorganic proton conductor for neuromorphic systems. Nat Commun, 2014, 5(1):40 https://arxiv.org/pdf/1311.0559.pdf
[13]
Park J S, Maeng W J, Kim H S, et al. Review of recent developments in amorphous oxide semiconductor thin-film transistor devices. Thin Solid Films, 2012, 520(6):1679 doi: 10.1016/j.tsf.2011.07.018
[14]
Zhou J M, Wang C J, Zhu L Q. Synaptic behaviors mimicked in flexible oxide-based transistors on plastic substrates. IEEE Electron Device Lett, 2013, 34(11):1433 doi: 10.1109/LED.2013.2280663
[15]
Guo L Q, Wan Q, Wang C J. Short-term memory to long-term memory transition mimicked in izo homojunction synaptic transistors. IEEE Electron Device Lett, 2013, 545(34):1581 http://industry.wanfangdata.com.cn/dl/Detail/NSTLQK?id=NSTLQK_NSTL_QKJJ0231075643
[16]
Zhou J M, Liu N, Zhu L Q. Energy-efficient artificial synapses based on flexible IGZO electric-double-layer transistors. IEEE Electron Device Lett, 2015, 36(2):198 doi: 10.1109/LED.2014.2381631
[17]
Zhu L Q, Cao J Y, Xiao H. Lateral protonic/electronic hybrid oxide thin-film transistor gated by SiO2 nanogranular films. Appl Phys Lett, 2014, 105(24):855 https://www.researchgate.net/publication/278323207_Lateral_protonicelectronic_hybrid_oxide_thin-film_transistor_gated_by_SiO2_nanogranular_films
[18]
Mazeau K, Rinaudo M. Comparative properties of hyaluronan and chitosan in aqueous environment. Prog Polym Sci, 2012, 54(1):96 doi: 10.1134%2FS1811238212070041.pdf
[19]
Zhang J, Dai J N, Zhu L Q. Laterally coupled IZO-based transistors on free-standing proton conducting chitosan membranes. IEEE Electron Device Lett, 2014, 35(8):838 doi: 10.1109/LED.2014.2332064
[20]
Liu Y H, Zhu L Q, Feng P. Freestanding artificial synapses based on laterally proton-coupled transistors on chitosan membranes. Adv Mater, 2015, 27(37):5599 doi: 10.1002/adma.201502719
[21]
Feng P, Wu G D, Schmitt O G, et al. Photosensitive hole transport in Schottky-contacted Si nanomembranes. Appl Phys Lett, 2014, 105(12):121101 doi: 10.1063/1.4896490
[22]
Zhang P P, Nordberg E P, Park B N, et al. Electrical conductivity in silicon nanomembranes. New J Phys, 2006, 8(9):297 doi: 10.1088/1367-2630/8/9/200/pdf
[23]
Qiu K, Zuo Y H, Zhou T W, et al. Enhanced light trapping in periodically truncated cone silicon nanowire structure. J Semicond, 2015, 36(10):104005 doi: 10.1088/1674-4926/36/10/104005
[24]
Kim H S, Won S M, Ha Y G, et al. Self-assembled nanodielectrics and silicon nanomembranes for low voltage, flexible transistors, and logic gates on plastic substrates. Appl Phys Lett, 2009, 95(18):183504 doi: 10.1063/1.3256223
[25]
Suganuma K, Watanabe S, Gotou T, et al. Fabrication of transparent and flexible organic field-effect transistors with solutionprocessed graphene source drain and gate electrodes. Appl Phys Express, 2011, 4(4):021603 https://www.researchgate.net/publication/230855035_Fabrication_of_Transparent_and_Flexible_Organic_Field-Effect_Transistors_with_Solution-Processed_Graphene_Source-Drain_and_Gate_Electrodes
[26]
Kumar M. A review of chitin and chitosan applications. React Funct Polym, 2000, 46(1):1 doi: 10.1016/S1381-5148(00)00038-9
[27]
Satake S I, Inoue T, Imoto K. Paired-pulse facilitation of multivesicular release and intersynaptic spillover of glutamate at rat cerebellar granule cell-interneurone synapses. J Physiol, 2012, 590(22):5653 doi: 10.1113/jphysiol.2012.234070
[28]
Liu N, Zhu L Q, Feng P, et al. Flexible sensory platform based on oxide-based neuromorphic transistors. Sci Rep, 2015, 5:18082 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4676022/
[29]
Wang C J, Zhu L Q, Zhou J M, et al. Memory and learning behaviors mimicked in nanogranular SiO2-based proton conductor gated oxide-based synaptic transistors. Nanoscale, 2013, 5(21):10194 doi: 10.1039/c3nr02987e
[30]
London M, Hausser M. Dendritic computation. Annu Rev Neurosci, 2005, 28:503 doi: 10.1146/annurev.neuro.28.061604.135703
[31]
Silver R A. Neuronal arithmetic. Nat Rev Neurosci, 2010, 11(7):474 doi: 10.1038/nrn2864

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    Received: 05 August 2016 Revised: 13 September 2016 Online: Published: 01 June 2017

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      Article Navigation >  Journal of Semiconductors  > 2017  >  38(6): 064006
      Minjie Liu, Gaoshan Huang, Ping Feng, Qinglei Guo, Feng Shao, Ziao Tian, Gongjin Li, Qing Wan, Yongfeng Mei. Artificial neuron synapse transistor based on silicon nanomembrane on plastic substrate[J]. Journal of Semiconductors, 2017, 38(6): 064006. doi: 10.1088/1674-4926/38/6/064006 ****M J Liu, G S Huang, P Feng, Q L Guo, F Shao, Z A Tian, G J Li, Q Wan, Y F Mei. Artificial neuron synapse transistor based on silicon nanomembrane on plastic substrate[J]. J. Semicond., 2017, 38(6): 064006. doi: 10.1088/1674-4926/38/6/064006.
      Citation:
      Minjie Liu, Gaoshan Huang, Ping Feng, Qinglei Guo, Feng Shao, Ziao Tian, Gongjin Li, Qing Wan, Yongfeng Mei. Artificial neuron synapse transistor based on silicon nanomembrane on plastic substrate[J]. Journal of Semiconductors, 2017, 38(6): 064006. doi: 10.1088/1674-4926/38/6/064006 ****
      M J Liu, G S Huang, P Feng, Q L Guo, F Shao, Z A Tian, G J Li, Q Wan, Y F Mei. Artificial neuron synapse transistor based on silicon nanomembrane on plastic substrate[J]. J. Semicond., 2017, 38(6): 064006. doi: 10.1088/1674-4926/38/6/064006.
      shu

      Artificial neuron synapse transistor based on silicon nanomembrane on plastic substrate

      DOI: 10.1088/1674-4926/38/6/064006
      • 1.

        Department of Materials Science, Fudan University, Shanghai 200433, China

      • 2.

        School of Electronic Science and Engineering and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China

      Funds:

      by the National Natural Science Foundation of China No. 51322201

      Project supported by the National Natural Science Foundation of China (No. 51322201), the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20120071110025), and Science and Technology Commission of Shanghai Municipality (No. 14JC1400200)

      Science and Technology Commission of Shanghai Municipality No. 14JC1400200

      the Specialized Research Fund for the Doctoral Program of Higher Education No. 20120071110025

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