Journal of Inorganic Materials ›› 2023, Vol. 38 ›› Issue (4): 445-451.DOI: 10.15541/jim20220767

• Topical Section on Neuromorphic Materials and Devices (Contributing Editor: WAN Qing) • Previous Articles     Next Articles

Dual-gate IGZO-based Neuromorphic Transistors with Stacked Al2O3/Chitosan Gate Dielectrics

WANG Jingyu1(), WAN Changjin1, WAN Qing1,2()   

  1. 1. School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China
    2. School of Micro-Nano Electronics, Zhejiang University, Hangzhou 310027, China
  • Received:2022-12-21 Revised:2023-01-17 Published:2023-04-20 Online:2023-02-07
  • Contact: WAN Qing, professor. E-mail:
  • About author:WANG Jingyu (1998-), female, Master candidate. E-mail:
  • Supported by:
    National Key Research and Development Program(2019YFB2205400);National Natural Science Foundation of China(62074075);National Natural Science Foundation of China(61834001)


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.

Key words: neuromorphic device, IGZO-based transistor, artificial synapse, stacked gate dielectric, high-k dielectric, synaptic plasticity

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