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© 2023 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

Dopamine is a catecholamine neurotransmitter that plays a significant role in the human central nervous system, even at extremely low concentrations. Several studies have focused on rapid and accurate detection of dopamine levels using field-effect transistor (FET)-based sensors. However, conventional approaches have poor dopamine sensitivity with values <11 mV/log [DA]. Hence, it is necessary to increase the sensitivity of FET-based dopamine sensors. In the present study, we proposed a high-performance dopamine-sensitive biosensor platform based on dual-gate FET on a silicon-on-insulator substrate. This proposed biosensor overcame the limitations of conventional approaches. The biosensor platform consisted of a dual-gate FET transducer unit and a dopamine-sensitive extended gate sensing unit. The capacitive coupling between the top- and bottom-gate of the transducer unit allowed for self-amplification of the dopamine sensitivity, resulting in an increased sensitivity of 373.98 mV/log[DA] from concentrations 10 fM to 1 μM. Therefore, the proposed FET-based dopamine sensor is expected to be widely applied as a highly sensitive and reliable biosensor platform, enabling fast and accurate detection of dopamine levels in various applications such as medical diagnosis and drug development.

Details

Title
High-Performance FET-Based Dopamine-Sensitive Biosensor Platform Based on SOI Substrate
Author
Tae-Hwan Hyun  VIAFID ORCID Logo  ; Won-Ju, Cho  VIAFID ORCID Logo 
First page
516
Publication year
2023
Publication date
2023
Publisher
MDPI AG
e-ISSN
20796374
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2819360338
Copyright
© 2023 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.