Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/170497
Title: Highly sensitive transistor sensor for biochemical sensing and health monitoring applications: a review
Authors: Moudgil, Akshay
Leong, Wei Lin
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2023
Source: Moudgil, A. & Leong, W. L. (2023). Highly sensitive transistor sensor for biochemical sensing and health monitoring applications: a review. IEEE Sensors Journal, 23(8), 8028-8041. https://dx.doi.org/10.1109/JSEN.2023.3253841
Project: RG118/21 
Journal: IEEE Sensors Journal 
Abstract: Transistors have gained tremendous attraction in biochemical sensing due to their outstanding performance with high sensitivity, flexibility, selectivity, real-time monitoring, ease of fabrication, and biocompatibility for various point-of-care biomedical and healthcare applications. Herein, critical sensing capability by different transistor classes of i) organic field-effect transistor, ii) organic electrochemical transistor, iii) low dimensional semiconductor field-effect transistor, and iv) hybrid transistors are summarized for biochemical (e.g., ions, glucose, antigen/antibody, DNA, bacteria, virus, cancer biomarkers) detection. Recent advancements in the transistor field for bioanalyte sensing, including a new class of a photoelectrochemical transistor, bioreceptor conjugation, strategies to improve sensitivity and overcoming the limit of detection are discussed in a focused manner. Furthermore, organic and inorganic active material-based transistors are compared to find the best fit for specific target bio-detection and healthcare applications.
URI: https://hdl.handle.net/10356/170497
ISSN: 1530-437X
DOI: 10.1109/JSEN.2023.3253841
DOI (Related Dataset): 10.21979/N9/D0J0UM
Schools: School of Electrical and Electronic Engineering 
Rights: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/JSEN.2023.3253841.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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