Issue 4, 2023

Recent trends in carbon nanotube (CNT)-based biosensors for the fast and sensitive detection of human viruses: a critical review

Abstract

The current COVID-19 pandemic, with its numerous variants including Omicron which is 50–70% more transmissible than the previously dominant Delta variant, demands a fast, robust, cheap, and easily deployed identification strategy to reduce the chain of transmission, for which biosensors have been shown as a feasible solution at the laboratory scale. The use of nanomaterials has significantly enhanced the performance of biosensors, and the addition of CNTs has increased detection capabilities to an unrivaled level. Among the various CNT-based detection systems, CNT-based field-effect transistors possess ultra-sensitivity and low-noise detection capacity, allowing for immediate analyte determination even in the presence of limited analyte concentrations, which would be typical of early infection stages. Recently, CNT field-effect transistor-type biosensors have been successfully used in the fast diagnosis of COVID-19, which has increased research and commercial interest in exploiting current developments of CNT field-effect transistors. Recent progress in the design and deployment of CNT-based biosensors for viral monitoring are covered in this paper, as are the remaining obstacles and prospects. This work also highlights the enormous potential for synergistic effects of CNTs used in combination with other nanomaterials for viral detection.

Graphical abstract: Recent trends in carbon nanotube (CNT)-based biosensors for the fast and sensitive detection of human viruses: a critical review

Associated articles

Article information

Article type
Review Article
Submitted
15 4 2022
Accepted
13 10 2022
First published
09 11 2022
This article is Open Access
Creative Commons BY license

Nanoscale Adv., 2023,5, 992-1010

Recent trends in carbon nanotube (CNT)-based biosensors for the fast and sensitive detection of human viruses: a critical review

H. Meskher, H. C. Mustansar, A. K. Thakur, R. Sathyamurthy, I. Lynch, P. Singh, T. K. Han and R. Saidur, Nanoscale Adv., 2023, 5, 992 DOI: 10.1039/D2NA00236A

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