A Review of Piezoelectric and Magnetostrictive Biosensor Materials for Detection of COVID-19 and Other Viruses

Fumio Narita*, Zhenjin Wang, Hiroki Kurita, Zhen Li, Yu Shi, Yu Jia, Constantinos Soutis

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

The spread of the severe acute respiratory syndrome coronavirus has changed the lives of people around the world with a huge impact on economies and societies. The development of wearable sensors that can continuously monitor the environment for viruses may become an important research area. Here, the state of the art of research on biosensor materials for virus detection is reviewed. A general description of the principles for virus detection is included, along with a critique of the experimental work dedicated to various virus sensors, and a summary of their detection limitations. The piezoelectric sensors used for the detection of human papilloma, vaccinia, dengue, Ebola, influenza A, human immunodeficiency, and hepatitis B viruses are examined in the first section; then the second part deals with magnetostrictive sensors for the detection of bacterial spores, proteins, and classical swine fever. In addition, progress related to early detection of COVID-19 (coronavirus disease 2019) is discussed in the final section, where remaining challenges in the field are also identified. It is believed that this review will guide material researchers in their future work of developing smart biosensors, which can further improve detection sensitivity in monitoring currently known and future virus threats.

Original languageEnglish
Article number2005448
JournalAdvanced Materials
Volume33
Issue number1
Early online date24 Nov 2020
DOIs
Publication statusPublished - 7 Jan 2021

Bibliographical note

© 2020 The Authors. Advanced Materials published by Wiley‐VCH GmbH

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Funding Information:
The authors greatly acknowledge the support of this work by Japan Society for the Promotion of Science (JSPS), Core‐to‐Core Program, grant number: JPJSCCA20200005.

Keywords

  • artificial intelligence
  • biosensors
  • data analytics
  • detection properties
  • electromagneto-mechanical design
  • Internet of Things
  • machine learning
  • piezoelectric/magnetostrictive materials
  • virus

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