• Journal of Inorganic Materials
  • Vol. 38, Issue 4, 445 (2023)
Jingyu WANG1, Changjin WAN1, and Qing WAN1、2、*
Author Affiliations
  • 11. School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China
  • 22. School of Micro-Nano Electronics, Zhejiang University, Hangzhou 310027, China
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    DOI: 10.15541/jim20220767 Cite this Article
    Jingyu WANG, Changjin WAN, Qing WAN. Dual-gate IGZO-based Neuromorphic Transistors with Stacked Al2O3/Chitosan Gate Dielectrics [J]. Journal of Inorganic Materials, 2023, 38(4): 445 Copy Citation Text show less

    Abstract

    Indium-gallium-zinc-oxide (IGZO)-based electric-double-layer (EDL) transistors have great applications for neuromorphic perception and computing systems because of their low processing temperature, high homogeneity, and plentiful ionic dynamics. However, IGZO-based EDL transistors have problems of high leakage current (>10 nA), high energy consumption and abnormal current spikes, which are the main obstacles to the development of neuromorphic computing systems based on such devices. In this work, a novel IGZO neuromorphic transistor with Al2O3/chitosan stacked gate dielectric was proposed. Compared with the monolayer chitosan gate dielectric transistor, the device with Al2O3/chitosan layer showed low subthreshold swing of 78.3 mV/decade, a low gate leakage current of 1.3 nA (reduced by about 98%), a large hysteresis window of 3.73 V (increased by about 3.4 times), a low excitable postsynaptic current of 0.86 nA (decreased by about 97%) and an energy consumption of 1.7 pJ for a spike event (0.5 V, 20 ms). Additionally, the emulation of spiking synaptic function and the synergistically modulation of the channel current were also realized, and the abnormal current spike caused by high leakage in synaptic plasticity simulation was also effectively avoided. The results suggest that the inserting of high-k dielectric layer can effectively improve the leakage current, energy consumption and performance of neuromorphic devices, which has substantial value for future ultra-low energy consumption neuromorphic perception and computing systems.
    Jingyu WANG, Changjin WAN, Qing WAN. Dual-gate IGZO-based Neuromorphic Transistors with Stacked Al2O3/Chitosan Gate Dielectrics [J]. Journal of Inorganic Materials, 2023, 38(4): 445
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