A recent study presented an AI-enhanced NIRS-XRF fusion spectroscopy method that significantly improves coal classification and quality prediction for coking enterprises.

A new review in Digital Discovery by Yongqiang Cheng of MIT and Oak Ridge National Laboratory highlights how AI-driven methods are changing how we study atomic vibrations.

This Icons of Spectroscopy Series article features E. Bright Wilson, a pioneer of chemical physics. Wilson’s contributions to infrared, Raman, and microwave spectroscopy provided the theoretical and practical foundation for analyzing molecular structure and dynamics. As a revered professor at Harvard and coauthor of landmark texts, he mentored nearly 150 students and researchers, leaving a lasting legacy of scientific excellence and integrity.

In this column, we will describe what is known about the structures of these materials and how Raman spectroscopy can characterize them.

ATR FT-IR shows polyethylene and polypropylene particles were common in facial scrubs and creams.

Top articles published this week include a tutorial about calibration transfer techniques and inter-instrument variability, a couple news articles about quantifying microplastics, and a feature on the “pressure to publish.”

Researchers from the U.S. Horticultural Research Laboratory’s Agricultural Research Service present a preliminary characterization of the citrus peel materials responsible for elevated high performance liquid chromatography-ultraviolet (HPLC-UV) chromatogram baselines from citrus peel extracts through the use of Fourier-transform infrared (FTIR) and proton-nuclear magnetic resonance (1H-NMR) spectroscopy.

Chinese Academy of Sciences researchers combine spectroscopic methods with deep learning to classify microplastics at near-perfect accuracy.

A new study uses spectroscopic tools to analyze the spread and transformation of microplastics across water, soil, and air systems. Researchers also examined the limitations of global policies in addressing this multidimensional pollutant.

Researchers from Zhejiang University highlight how combining machine learning with spectroscopic imaging can transform biomedical research by enabling more precise, interpretable, and efficient analysis of complex molecular data.

Jiangnan University researchers map the evolution, challenges, and future of spectroscopy in preserving humanity’s shared legacy.

The findings suggest that bottling processes and PET containers are major contributors to beverage contamination, raising concerns about food safety and environmental pollution.

A new study by researchers from Spain and Brazil demonstrates that combining near- and mid-infrared spectroscopy with advanced statistical analysis can identify how growing site, harvest season, and clonal variation influence yerba mate’s chemical composition.