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Jang, Jaesung
Sensors & Aerosols Lab.
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Sensitive and highly rapid electrochemical measurement of airborne coronaviruses through condensation-based direct impaction onto carbon nanotube-coated porous paper working electrodes

Author(s)
Lee, DaesoonJang, JunbeomJang, Jaesung
Issued Date
2023-09
DOI
10.1016/j.jhazmat.2023.131972
URI
https://scholarworks.unist.ac.kr/handle/201301/64768
Citation
JOURNAL OF HAZARDOUS MATERIALS, v.458, pp.131972
Abstract
Rapid detection of indoor airborne viruses is critical to prevent the spread of respiratory diseases. Herein, we present sensitive, highly rapid electrochemical measurement of airborne coronaviruses through condensation-based direct impaction onto antibody-immobilized, carbon nanotube-coated porous paper working electrodes (PWEs). Carboxylated carbon nanotubes are drop-cast on paper fibers to make three-dimensional (3D) porous PWEs. These PWEs have higher active surface area-to-volume ratios and electron transfer characteristics than conventional screen-printed electrodes. The limit of detection and detection time of the PWEs for liquid-borne coronaviruses OC43 are 65.7 plaque-forming units (PFU)/mL and 2 min, respectively. The PWEs showed sensitive and rapid detection of whole coronaviruses, which can be ascribed to the 3D porous electrode structure of the PWEs. Moreover, water molecules condense on airborne virus particles during air sampling, and these water-encapsulated virus particles (<4 µm) are impacted on the PWE for direct measurement without virus lysis and elution. The whole detection takes ∼10 min, including air sampling, at virus concentrations of 1.8 and 11.5 PFU/L of air, which can be due to the highly enriching and minimally damaging virus capture on a soft and porous PWE, demonstrating the potential for the rapid and low-cost airborne virus monitoring system.
Publisher
Elsevier BV
ISSN
0304-3894
Keyword (Author)
Indoor airAirborne virus monitoringRespiratory virusesPaper-based sensorCondensation-based air sampler
Keyword
INFLUENZA-VIRUSNANOPARTICLESIMMUNOSENSORFLOW

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