JOURNAL ARTICLE

Artificial Synapse Emulated through Fully Aqueous Solution-Processed Low-Voltage In2O3 Thin-Film Transistor with Gd2O3 Solid Electrolyte

You-Hang ZhouJun LiYaohua YangQi ChenJianhua Zhang

Year: 2019 Journal:   ACS Applied Materials & Interfaces Vol: 12 (1)Pages: 980-988   Publisher: American Chemical Society

Abstract

Brain-like neuromorphic computing system provides an alternative approach for the future computer for its characteristics of high-efficiency, power-efficient, self-learning, and parallel computing. Therefore, the imitation of synapse behavior based on microelectronics is particularly important. Recently, the synaptic transistors have received widespread attention. Among them, solid oxide-based synaptic transistors are more compatible with the large-scale fabrication than the liquid and organic-based transistors. So the development of oxide synaptic transistor is required. Here, a novel aqueous solution-processed Gd2O3 is suggested to be the solid electrolyte for synaptic transistors. The microstructure and the dielectric properties of Gd2O3 film are investigated, which show the potential for the simulation of synaptic transmission. Then, the fully aqueous solution-processed In2O3/Gd2O3 thin-film transistor (TFT) is fabricated. The device exhibits an acceptable electrical performance with a small threshold voltage of 1.24 V, and a small subthreshold swing of 0.12 V/decade. The artificial synapse behavior is stimulated and the short-term plasticity of In2O3/Gd2O3 TFT is studied. The dependence of its excitatory postsynaptic current on presynaptic pulse magnitude, width, and frequency is verified. Besides, the synapse behavior of devices under continuous illumination stresses is investigated. The lights with different photon energy have different effects on the synaptic transmission, which is related to the ionization of oxygen vacancies. Our results demonstrate that fully aqueous solution-processed In2O3 TFT with Gd2O3 solid electrolyte is a candidate for the synaptic transistor.

Keywords:
Materials science Transistor Thin-film transistor Optoelectronics Neuromorphic engineering Synapse Nanotechnology Voltage Computer science Electrical engineering Neuroscience Artificial neural network

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Citation History

Topics

Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Thin-Film Transistor Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
CCD and CMOS Imaging Sensors
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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