Ishan Barman, an associate professor of mechanical engineering, who, along with David Gracias, professor of chemical and biomolecular engineering, are the lead authors of the study.
Proven sensor 92% accuracy when detecting SARS-COV-2 in saliva samples – comparable to a PCR test.
“Our platform goes beyond the current COVID-19 pandemic. We can use this to test broadly against different viruses, for example to differentiate between SARS-CoV- 2 and H1N1, and even variants. This is a big problem that cannot be easily solved by current rapid tests,” Barman said.