Wang, QN, Zhao, C, Liu, W, Mitrovic, IZ ORCID: 0000-0003-4816-8905, van Zalinge, H ORCID: 0000-0003-0996-1281, Liu, YN and Zhao, CZ
(2022)
Synaptic transistors based on transparent oxide for neural image recognition.
SOLID-STATE ELECTRONICS, 194.
p. 108342.
Text
SSE_Manuscript.docx - Author Accepted Manuscript Download (1MB) |
Abstract
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.
Item Type: | Article |
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Uncontrolled Keywords: | Image recognition, Solution-processed transistor, Synaptic device, MNIST, Neural computing |
Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science Faculty of Science and Engineering > School of Physical Sciences |
Depositing User: | Symplectic Admin |
Date Deposited: | 23 May 2022 15:29 |
Last Modified: | 21 Apr 2023 01:30 |
DOI: | 10.1016/j.sse.2022.108342 |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3155324 |