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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

In this study, we propose tunable pH sensors based on the electric-double-layer transistor (EDLT) with time-dependent sensitivity characteristics. The EDLT is able to modulate the drain current by using the mobile ions inside the electrolytic gate dielectric. This property allows the implementation of a device with sensitivity characteristics that are simply adjusted according to the measurement time. An extended gate-type, ion-sensitive, field-effect transistor consisting of a chitosan/Ta2O5 hybrid dielectric EDLT transducer, and an SnO2 sensing membrane, were fabricated to evaluate the sensing behavior at different buffer pH levels. As a result, we were able to achieve tunable sensitivity by only adjusting the measurement time by using a single EDLT and without additional gate electrodes. In addition, to demonstrate the unique sensing behavior of the time-dependent tunable pH sensors based on organic–inorganic hybrid EDLT, comparative sensors consisting of a normal FET with a SiO2 gate dielectric were prepared. It was found that the proposed pH sensors exhibit repeatable and stable sensing operations with drain current deviations <1%. Therefore, pH sensors using a chitosan electrolytic EDLT are suitable for biosensor platforms, possessing tunable sensitivity and high-reliability characteristics.

Details

Title
Time-Dependent Sensitivity Tunable pH Sensors Based on the Organic-Inorganic Hybrid Electric-Double-Layer Transistor
Author
Park, Ki-Woong  VIAFID ORCID Logo  ; Won-Ju, Cho  VIAFID ORCID Logo 
First page
10842
Publication year
2022
Publication date
2022
Publisher
MDPI AG
ISSN
16616596
e-ISSN
14220067
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2716558570
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.