JILA and NIST Fellows David Nesbitt's and Jun Ye's recent results in their breathalyzer study have been highlighted in a new article in Scientific American. Using frequency combs, a particular type of laser array, scientists could detect specific molecules in the breath, including diseases like COVID-19. This research suggests huge implications for the future of disease diagnosis and prevention. “We are training our frequency comb nose using machine learning, and once it’s trained, it becomes an electronic dog—with much greater sensitivity,” Ye says in the article.
Read the full article here.