Vol 30 No 12 Spectroscopy December 2015 Regular Issue PDF

During EAS 2024, we interviewed Igor Lednev of the University of Albany about his storied career and his expectations for 2025.

Researchers from Stanford University have combined surface-enhanced Raman spectroscopy (SERS) with machine learning (ML) to enable rapid, precise single-cell analysis, offering potentially transformative applications in diagnostics and personalized medicine.

Light is utilized in a wide range of spectroscopic techniques and practices to gain a variety of information about materials and chemicals. These analyses can include material/chemical identification, quantitative analysis, quality control/quality assurance testing, and biological studies, among other applications. Applications, along with sample handling for both FTIR and UV-Vis spectroscopy, will be outlined in this paper.

A recent study examined the role that Raman spectroscopy is playing in disease diagnosis.