Synaptic transistors based on transparent oxide for neural image recognition

Q. N. Wang, C. Zhao*, W. Liu, I. Z. Mitrovic, H. van Zalinge, Y. N. Liu, C. Z. Zhao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Artificial synaptic devices are the critical component for large-scale neuromorphic computing, which surpasses the limitations of von Neumann's structure. Recently the emerging electrolyte gated transistor (EGT) has proven to be a promising neuromorphic application due to the conductance can be updated by the gate voltage stimulation. This paper presents a new low-temperature solution-based oxide thin film transistor with lithium (Li) ion dope dinto dielectric layer. We have proposed the indium oxide (InOx)/ zirconia (ZrOx) transistor with large hysteresis. The synaptic plasticity of EGTs demonstrate the potential to simulate the biological neuron and calculation function. Moreover, the inhibitory/excitatory postsynaptic current (IPSC/EPSC), long-term potentiation/depression (LTP/LTD), short-term potentiation (STP), and paired-pulse facilitation (PPF) are confirmed through the electrical stimulation. The suitable ion doping concentration is obtained by the synaptic electrical characteristic. The synaptic transistor also has a low-noise linear conductance update and a relatively high Gmax/Gmin ratio. According to the Gmax/Gmin ratio and nonlinearity, the weight update process can be simulated for neuromorphic computing.

Original languageEnglish
Article number108342
JournalSolid-State Electronics
Publication statusPublished - Aug 2022


  • Image recognition
  • Neural computing
  • Solution-processed transistor
  • Synaptic device


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