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Environ Sci Technol. 2011 Sep 1;45(17):7473-80. doi: 10.1021/es1043547. Epub 2011 Aug 1.

Integrating silicon nanowire field effect transistor, microfluidics and air sampling techniques for real-time monitoring biological aerosols.

Author information

1
State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.

Abstract

Numerous threats from biological aerosol exposures, such as those from H1N1 influenza, SARS, bird flu, and bioterrorism activities necessitate the development of a real-time bioaerosol sensing system, which however is a long-standing challenge in the field. Here, we developed a real-time monitoring system for airborne influenza H3N2 viruses by integrating electronically addressable silicon nanowire (SiNW) sensor devices, microfluidics and bioaerosol-to-hydrosol air sampling techniques. When airborne influenza H3N2 virus samples were collected and delivered to antibody-modified SiNW devices, discrete nanowire conductance changes were observed within seconds. In contrast, the conductance levels remained relatively unchanged when indoor air or clean air samples were delivered. A 10-fold increase in virus concentration was found to give rise to about 20-30% increase in the sensor response. The selectivity of the sensing device was successfully demonstrated using H1N1 viruses and house dust allergens. From the simulated aerosol release to the detection, we observed a time scale of 1-2 min. Quantitative polymerase chain reaction (qPCR) tests revealed that higher virus concentrations in the air samples generally corresponded to higher conductance levels in the SiNW devices. In addition, the display of detection data on remote platforms such as cell phone and computer was also successfully demonstrated with a wireless module. The work here is expected to lead to innovative methods for biological aerosol monitoring, and further improvements in each of the integrated elements could extend the system to real world applications.

PMID:
21780777
DOI:
10.1021/es1043547
[Indexed for MEDLINE]

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