A method of highly accurate and sensitive virus identification using Raman spectroscopy, a portable virus capture device and machine learning could enable real-time virus detection and identification to help battle future pandemics, according to a team of researchers led by Penn State.
“This virus detection method is label-free and not aimed at any specific virus, thus enabling us to identify potential new strains of viruses,” said Shengxi Huang, assistant professor of electrical engineering and biomedical engineering and co-author of the study that appeared today (June 2) in the Proceedings of the National Academy of Sciences. “It is also rapid, so suitable for fast screening in crowded public spaces. In addition, the rich Raman features together with machine learning analysis enable a deeper understanding of the virus structures.”
Raman spectroscopy detects unique vibrations in molecules by picking up shifts when a laser light beam induces these vibrations. To capture the viruses, a tool known as a microfluidic device would be used to trap viruses between forests of aligned carbon nanotubes.
Microfluidic devices use very small amounts of body fluids on a microchip to do medical and laboratory tests. Such a device could use virus cultures, saliva, nasal washes, or even exhaled breath, including samples gathered on-site during an outbreak. The carbon nanotubes forests would filter out any foreign substance or background molecules from the host or surrounding air that could make it more difficult to get an accurate reading.









