A new review article highlights the role Fourier transform infrared (FT-IR) spectroscopy plays in characterizing nanomaterials and polymers.

Researchers from the University of Copenhagen (Denmark) are using chromatography and spectroscopy combined to help predict wine ratings. The team investigated the relationship between chemical composition and consumer liking, using Vivino ratings as quality endpoints.

Researchers from China Agricultural University introduce PeaNet, promising rapid, accurate, and nondestructive protein analysis.

Chinese researchers have developed a cutting-edge cervical cancer diagnostic model that combines spontaneous Raman spectroscopy, CARS imaging, and artificial intelligence to achieve 100% accuracy in distinguishing healthy and cancerous tissue.

Researchers at the University of Belgrade have demonstrated that combining Raman and FT-IR spectroscopy with machine learning algorithms offers a highly accurate, non-destructive method for identifying seed varieties in lettuce, paprika, and tomato.

A compilation of articles that explore the role of Raman spectroscopy in cancer research is presented.

A new comparative study shows that scientific CMOS (sCMOS) cameras could rival traditional CCD detectors in certain Raman CARS spectroscopy applications, offering faster readout and dynamic range despite slightly higher noise levels.

Researchers from Guangdong Polytechnic Normal University highlight how combining Raman spectroscopy with machine learning enables rapid, non-destructive, and highly accurate analysis of fruit quality, offering transformative potential for food safety and agricultural diagnostics.

DOGE-related federal funding cuts have sharply reduced salaries, lab budgets, and graduate support in academia. Researchers view the politically driven shifts in priorities as part of recurring systemic issues in U.S. science funding during administrative transitions. The impact on Federal laboratories has varied, with some seeing immediate effects and others experiencing more gradual effects. In general, there is rising uncertainty over future appropriations. Sustainable recovery may require structural reforms, leaner administration, and stronger industry-academia collaboration. New commentary underscores similar challenges, noting scaled-back graduate admissions, spending freezes, and a pervasive sense of overwhelming stress among faculty, students, and staff. This article addresses these issues for the analytical chemistry community.

Published in Food Chemistry, researchers from Jiangsu University of Science and Technology and Jimei University use near-infrared (NIR) spectroscopy and machine learning to tackle food adulteration and enhance quality control.

Top articles published this week include an interview series with Robert Ewing of the Pacific Northwest National Laboratory, a news article on using infrared (IR) cameras to see invisible methane leaks, and an article about the role of vibrational spectroscopy in analyzing plant-based food products.

In Part II of our three-part interview with Robert Ewing, he reviews the results of the Nogales border test.

Researchers at Heilongjiang University have developed a rapid and accurate method for detecting sweeteners in food using Raman spectroscopy combined with a Random Forest machine learning algorithm, offering a powerful tool for improving food safety.