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 have developed a powerful deep learning model that automates the identification of minerals using Raman spectroscopy, offering faster, more accurate results even in complex geological samples. By integrating attention mechanisms and explainable AI tools, the system boosts trust and performance in field-based mineral analysis.

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.

A new review by researchers from IIT Delhi and the University of Queensland highlights how Terahertz (THz) and low-wavenumber Raman (THz-Raman) spectroscopy are advancing quality control and efficiency in pharmaceuticals, agriculture, and mineral industries. These powerful non-invasive tools enable detailed multi-parameter sensing, offering deeper insight at the molecular level.

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.

A team of international researchers has developed a faster, more accurate method to analyze soil carbon fractions using mid-infrared spectroscopy and deep learning. Their approach preserves the chemical balance of soil organic carbon components, paving the way for improved climate models and sustainable land management.

The 78th International Symposium on Molecular Spectroscopy (ISMS) is set to take place this year from June 23rd to 27th, 2025. Here is what attendees can expect.

In the first part of this three-part interview, Ayanjeet Ghosh of the University of Alabama and Rohit Bhargava of the University of Illinois Urbana-Champaign discuss their interest in using discrete frequency infrared (IR) imaging to analyze protein secondary structures.

Top articles published this week include a new Icons of Spectroscopy column, a news story about the use of Fourier transform infrared (FT-IR) spectroscopy in gemology, and a Q&A interview about elemental analysis in pharmaceutical analysis.

In this final part of our conversation with Harrington and Seibert, they discuss the main challenges that they encountered in their study and how we can improve elemental impurity analysis in pharmaceutical quality control.