Raman Spectroscopy

A new study published in Green Analytical Chemistry reveals significant microplastic pollution in Uzbekistan’s Zarafshan River, highlighting regional differences, industrial contributions, and the urgent need for improved monitoring and mitigation strategies.

Last year, we released a content series titled “Advancing Agriculture for Future Generations.” Here, we compile some of the latest studies in this space.

Presentations held during the first half of SPIE Photonics West 2025 highlighted the latest technological advancements in spectroscopy and how they can improve quality of life for people around the world.

Researchers have demonstrated the potential of deep ultraviolet Raman spectroscopy (DUVRS) as a rapid, nondestructive, and sensitive tool for detecting antihistamines like cetirizine in oral fluid samples, paving the way for broader forensic applications.

This excerpt from The Concise Handbook of Analytical Spectroscopy, which spans five volumes, serves as a comprehensive reference, detailing the theory, instrumentation, sampling methods, experimental design, and data analysis techniques for each spectroscopic region.

To improve the robustness and accuracy of logistic regression identification method, a new Raman spectroscopy identification method was proposed that combines a distributionally robust optimization technique and fused lasso technique with logistic regression. Then, Raman spectroscopy was used to analyze two types of dairy products that were collected for anti-jamming identification testing to verify the effectiveness of the new method.

Researchers from Tsinghua University have developed an innovative dual-wavelength Raman spectroscopy method that eliminates fluorescence interference in measuring esophageal tissue samples. This development enables precise identification of molecular changes in these tissues, with potential applications in early esophageal cancer diagnosis.

A recent study from Shanghai University demonstrated aa novel method for identifying and quantifying animal-origin milk powders.

A new study highlights the use of Raman spectroscopy to detect lung cancer and evaluate the effects of the PCV13 vaccine. Researchers found distinct biochemical changes in lung cancer patients and healthy individuals, revealing the vaccine's significant impact on immune response.

Spectroscopy recently sat down with Isao Noda of the University of Delaware and Young Mee Jung of Kangwon National University to talk about the principles of two-dimensional correlation spectroscopy (2D-COS) and its key applications.

A recent study demonstrates the successful development of in-line monitoring techniques using Raman spectroscopy and advanced modeling for titanium dioxide-free tablet coatings.

A combination of surface-enhanced Raman spectroscopy (SERS) and machine learning on microfluidic chips has achieved an impressive 98.6% accuracy in classifying leukemia cell subtypes, offering a fast, highly sensitive tool for clinical diagnosis.

Researchers at the Chinese Academy of Sciences have developed an optical detection strategy for circulating tumor cells (CTCs), combining machine learning (ML) and dual-modal surface-enhanced Raman spectroscopy (SERS). This approach offers high sensitivity, specificity, and efficiency, potentially advancing early cancer diagnosis.

A recent study examined how Raman spectroscopy, when combined with machine learning (ML), can detect and analyze fertilizer nutrients.

Researchers from the University of Liege have demonstrated the potential of surface-enhanced transmission Raman spectroscopy (SETRS) for detecting impurities in pharmaceuticals. The study highlights SETRS’s superior sensitivity, precision, and efficiency in quantifying toxic impurities like 4-aminophenol (4-AP), offering a promising alternative to traditional methods.

Researchers have developed a rapid, reagent-free method to estimate the saponification value (SV) of edible oils using handheld Raman spectroscopy. This innovative approach simplifies oil quality testing, cutting time and costs while enhancing accuracy and portability.

Because there is a different Raman signature for each of the polymorphs as well as the contaminants, Raman microscopy is an ideal tool for analyzing the structure of these materials as well as identifying possible contaminants that would also interfere with performance.

In 2024, we launched multiple content series, covered major conferences, presented two awards, and continued our monthly Analytically Speaking episodes. Below, you'll find a selection of the most popular content from Spectroscopy over the past year.

This year-in-review showcases the standout technical articles, compelling interviews, and key news stories that defined the pages of Spectroscopy. In this year in review, the editors of Spectroscopy highlight some of the top published technical articles, interviews, and news content published.

Researchers from Italy have developed a Raman spectroscopy-based method for the rapid detection of Clostridium spores in milk. This technique offers significant advantages over traditional methods, reducing detection time by nearly half while maintaining sensitivity and reliability.

The world of engineering and innovation mourns the loss of a towering figure with the passing of Sir David McMurtry, CBE, RDI, FREng, FRS, CEng, FIMechE, co-founder and Non-Executive Director of Renishaw. Known for his brilliance, humility, and groundbreaking contributions to metrology and manufacturing, McMurtry leaves a legacy that has profoundly shaped modern engineering.

A recent study examined the role that Raman spectroscopy is playing in disease diagnosis.

Researchers at Yanshan University have developed a groundbreaking method combining Raman spectroscopy and deep learning models to accurately identify and quantify components in blended vegetable oils.

HSI is widely applied in fields such as remote sensing, environmental analysis, medicine, pharmaceuticals, forensics, material science, agriculture, and food science, driving advancements in research, development, and quality control.