Ecofriendly Solution-Combustion-Processed Thin-Film Transistors for Synaptic Emulation and Neuromorphic Computing.



Liu, Qihan, Zhao, Chun, Zhao, Tianshi, Liu, Yina, Mitrovic, Ivona Z ORCID: 0000-0003-4816-8905, Xu, Wangying, Yang, Li ORCID: 0000-0002-1040-4223 and Zhao, Ce Zhou
(2021) Ecofriendly Solution-Combustion-Processed Thin-Film Transistors for Synaptic Emulation and Neuromorphic Computing. ACS applied materials & interfaces.

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Abstract

The ecofriendly combustion synthesis (ECS) and self-combustion synthesis (ESCS) have been successfully utilized to deposit high-<i>k</i> aluminum oxide (AlO<i><sub>x</sub></i>) dielectrics at low temperatures and applied for aqueous In<sub>2</sub>O<sub>3</sub> thin-film transistors (TFTs) accordingly. The ECS and ESCS processes facilitate the formation of high-quality dielectrics at lower temperatures compared to conventional methods based on an ethanol precursor, as confirmed by thermal analysis and chemical composition characterization. The aqueous In<sub>2</sub>O<sub>3</sub> TFTs based on ECS and ESCS-AlO<i><sub>x</sub></i> show enhanced electrical characteristics and counterclockwise transfer-curve hysteresis. The memory-like counterclockwise behavior in the transfer curve modulated by the gate bias voltage is comparable to the signal modulation by the neurotransmitters. ECS and ESCS transistors are employed to perform synaptic emulation; various short-term and long-term memory functions are emulated with low operating voltages and high excitatory postsynaptic current levels. High stability and reproducibility are achieved within 240 pulses of long-term synaptic potentiation and depression. The synaptic emulation functions achieved in this work match the demand for artificial neural networks (ANN), and a multilayer perceptron (MLP) is developed using an ECS-AlO<i><sub>x</sub></i> synaptic transistor for image recognition. A superior recognition rate of over 90% is achieved based on ECS-AlO<i><sub>x</sub></i> synaptic transistors, which facilitates the implementation of the metal-oxide synaptic transistor for future neuromorphic computing via an ecofriendly route.

Item Type: Article
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: 01 Jun 2021 14:16
Last Modified: 06 Sep 2022 14:11
DOI: 10.1021/acsami.0c20947
URI: https://livrepository.liverpool.ac.uk/id/eprint/3121588