Top articles published this week include an interview with 2025 Clara Craver Award recipient Prashant Jain, an Icons of Spectroscopy column on Bruce R. Kowalski, and an interview with Pooja Sheevam about quantifying mineral basalts in the Hawaiian PTA-2 drill core.
In the final part of this video interview with Pooja Sheevam, she discusses the importance of her study in understanding the mineralogical and geochemical processes in Hawaii.
Researchers from Tianjin Agricultural University, Nankai University, and Zhejiang A&F University have developed a highly accurate method using near-infrared spectroscopy and machine learning to rapidly detect and classify microplastics in chicken feed.
Explore advancements in infrared spectroscopy and insights from Brian Smith, a key columnist, on the future of this evolving field.
In Part IV of our conversation with Pooja Sheevam, she discusses how scanning electron microscopy with an energy-dispersive X-ray spectroscopy (SEM-EDS) and bulk X-ray fluorescence (XRF) were used to better understand fluid-rock interactions.
Researchers use EC-SERS to reveal the first detailed structural study of hU-II peptide in aqueous solution, paving the way for new drug development.
A recent review in the Journal of Pharmaceutical Analysis highlights how AI, particularly deep learning, is revolutionizing Raman spectroscopy by enhancing its accuracy, efficiency, and applications in drug development, quality control, and clinical diagnostics.
In Part III, our discussion with Pooja Sheevam focused on the use of long-wave IR (LWIR) spectroscopy in analyzing basaltic rocks.
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 this interview segment, Pooja Sheevam elaborates on what LWIR and SWIR are and what advantages they both offer when analyzing Hawaiian geology.
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.
In this Q&A, Pooja Sheevam discusses why she used both long-wave infrared (LWIR) and short-wave IR (SWIR) spectroscopy in analyzing the PTA-2 drill core.
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.
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.
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.
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.
