Identification and quantitative detection of two pathogenic bacteria based on a terahertz metasensor
Bacterial infection can cause a series of diseases and play a vital role in medical care. Therefore, early diagnosis of pathogenic bacteria is crucial for effective treatment and the prevention of further infection. However, restricted by the current technology, bacterial detection is usually time-c...
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Veröffentlicht in: | Nanoscale 2023-01, Vol.15 (2), p.515-521 |
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Hauptverfasser: | , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Bacterial infection can cause a series of diseases and play a vital role in medical care. Therefore, early diagnosis of pathogenic bacteria is crucial for effective treatment and the prevention of further infection. However, restricted by the current technology, bacterial detection is usually time-consuming and laborious and the samples need tedious processing even to be tested. Herein, we present a terahertz metasensor based on the coupling of electrical and toroidal dipoles to achieve rapid, non-destructive, label-free identification and highly sensitive quantitative detection of the two most common pathogenic bacteria. The reinforcement of the toroidal dipole significantly boosts the light-matter interactions around the surface of the microstructure, and thus the sensitivity and
Q
factor of the designed metasensor reach as high as 378 GHz per refractive index unit (RIU) and 21.28, respectively. Combined with the aforementioned advantages, the proposed metasensor successfully identified
Escherichia coli
and
Staphylococcus aureus
and quantitatively detected four concentrations with the lowest detectable concentration being ∼10
4
cfu mL
−1
in the experiment. This work naturally enriches the research on THz metasensors based on the interference mechanism and inspires more innovations to facilitate the development of biosensing applications.
A terahertz (THz) metasensor based on the coupling of electric and toroidal dipoles achieves rapid, non-destructive, label-free identification and highly sensitive quantitative detection for the two most common pathogenic bacteria. |
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ISSN: | 2040-3364 2040-3372 |
DOI: | 10.1039/d2nr05038b |