A recent study examined the inner structure of calcium silicate hydrate, a principal binding agent in concrete.

Shanghai researchers develop high-accuracy machine learning system to identify colorless microplastics across varied environments.

A recent study explored new rapid screening alternatives to traditional methods for detecting pork adulteration in meatballs, aiding halal food authentication efforts.

In a paper published in Nature Communications (1), Prashant Jain and a team of researchers from the University of Illinois Urbana-Champaign (Urbana, Illinois) demonstrate how in situ nanoscale surface-enhanced Raman scattering (SERS) can reveal detailed surface chemistry during CO₂ reduction on silver (Ag) nanoparticles under photocatalytic conditions.Jain will receive the 2025 Clara Craver Award from the Coblentz Society, presented annually to an outstanding young molecular spectroscopist whose efforts are in applied analytical vibrational spectroscopy.

In this Icons of Spectroscopy article, Executive Editor Jerome Workman Jr. delves into the life and impact of Bruce Kowalski, an analytical chemist whose major contributions to chemometrics helped establish the field of applying advanced quantitative and qualitative mathematics to extract meaningful chemical information from complex datasets. Kowalski’s visionary approach to chemical data analysis, education, and software development has transformed the landscape of modern analytical chemistry for academia and industry.

Top articles published this week include an interview with Pooja Sheevam about her study analyzing Hawaii’s PTA-2 drill core, several news stories on recent meteorite studies, and a news article on using Raman spectroscopy and artificial intelligence (AI) to detect adulteration in maple syrup.

In Part I of our video interview with Pooja Sheevam, she discusses why she and her team used both LWIR and SWIR spectroscopy in analyzing Hawaii's PTA-2 drill core, and how the two techniques complemented each other in the study.

A proposed solution is a coal species classification method that combines terahertz time-domain spectroscopy with machine learning - specifically, principal component analysis (PCA) and cluster analysis (CA). By using terahertz (THz) time-domain spectroscopy (TDS), the absorption coefficient, dielectric constant, and refractive index of each sample were obtained from lignite, bituminous coal, and anthracite samples.

A new study published in Marine Pollution Bulletin reveals significant microplastic contamination at 5000-meter depths in the Central Indian Ocean Basin, highlighting the widespread reach of plastic pollution and the urgent need for regulatory action.

Researchers in China have pioneered a rapid, green, and non-destructive detection system using NIR spectroscopy and machine learning to ensure yak milk powder quality.

A new study published in the Journal of Food Composition and Analysis by researchers at the University of Sharjah reveals that while most cat foods sold in Sharjah meet international safety standards, some contain elevated metal levels, prompting calls for stricter regulation and quality control to protect pet health.

Researchers from Tohoku University, Shibaura Institute of Technology, and Shizuoka University unveil advanced sorting system using NIR, THz, and machine learning for improved recycling outcomes.

Researchers at McGill University have developed a fast, eco-friendly method using portable Raman spectroscopy and deep learning to accurately assess the antioxidant content of maple syrup on-site.

This work shows the great potential of mushrooms as excellent raw materials in the development of multifunctional fluorescence carbon materials.

Top articles published this week include an interview with Ayanjeet Ghosh and Rohit Bhargava on imaging for biomedical applications, a preview of the 78th International Symposium on Molecular Spectroscopy, and a news article on using artificial intelligence (AI) to study minerals.

Researchers at Guangdong University of Technology have developed a fast, non-destructive Raman spectroscopy method to accurately detect active ingredients in complex drug formulations.

On Wednesday, May 21st, 2025, Waters Corporation announced in a press release that they have acquired Halo Labs, which is a venture-backed company that produces imaging-based particle analysis technologies.

Surface hardness is one of the most important parameters which describes the degree of aging in polyvinyl chloride (PVC) cables. In this work, the hardness of PVC sheathing material was studied using laser-induced breakdown spectroscopy (LIBS).

A recent study published in the Journal of Archaeological Science: Reports reveals that a multi-headed snake motif at Argentina's La Candelaria rock shelter was created through multiple painting events over time.

A new review in TrAC Trends in Analytical Chemistry by Alfred Chin Yen Tay and Liang Wang highlights how machine learning (ML) is transforming surface-enhanced Raman spectroscopy (SERS) into a powerful, clinically viable tool for rapid and accurate medical diagnostics.

A study published in Chemosphere by researchers at the Technical University of Denmark demonstrates that fluorescence spectroscopy can serve as a rapid, on-site screening tool for detecting pharmaceutical contaminants in groundwater.

Researchers from several Chinese universities have developed a low-cost, red mud-based catalyst doped with manganese oxides that efficiently oxidizes toluene at lower temperatures, offering a sustainable solution for air pollution control and industrial waste reuse.

Researchers proposed Raman spectroscopy (RS) as a tool to obtain the biochemical profile of circulating extracellular vesicles in the context of breast cancer.

In the final part of this three-part interview, Ayanjeet Ghosh of the University of Alabama and Rohit Bhargava of the University of Illinois Urbana-Champaign talk about the key performance metrics they used to evaluate their model, and what the future of neurodegenerative disease research looks like.

Researchers from Tsinghua and Hainan Universities have developed a portable, non-destructive method using NIR spectroscopy, hyperspectral imaging, and machine learning to accurately assess the quality and detect adulteration in whey protein supplements.

In the second part of this three-part interview, Ayanjeet Ghosh of the University of Alabama and Rohit Bhargava of the University of Illinois Urbana-Champaign discuss how machine learning (ML) is used in data analysis and go into more detail about the model they developed in their study.