
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.
Jerome Workman, Jr. is an Executive Editor for Spectroscopy. Direct correspondence about this article to jworkman@mjhlifesciences.com

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.

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.


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.

A recent study by researchers from the University of Belgrade highlights the transformative potential of attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy for analyzing protein structures. This versatile method not only provides insights into secondary structures but also excels at tracking aggregation processes, offering advantages over traditional techniques like X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy.

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 new model corrects errors in analyzing complex mixtures using ATR FT-IR, paving the way for more accurate chemical insights.

Scientists have developed a novel and creative mid-infrared (MIR) hyperspectral microscope using single-pixel imaging (SPI) technology and a quantum cascade laser (QCL). This innovation offers faster, more cost-effective chemical analysis compared to traditional methods, promising new frontiers in microscopic imaging.

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.

This review provides an overview of LIB technology, and the spectroscopic techniques employed in LIB analysis.

The following is a summary of selected articles published recently in Spectroscopy on the subject of handheld, portable, and wearable spectrometers representing a variety of analytical techniques and applications. Here we take a closer look at the ever shrinking world of spectroscopy devices and how they are used. As spectrometers progress from bulky lab instruments to compact, portable, and even wearable devices, the future of spectroscopy is transforming dramatically. These advancements enable real-time, on-site analysis across diverse industries, from healthcare to environmental monitoring. This summary article explores cutting-edge developments in miniaturized spectrometers and their expanding range of practical applications.

Over the past two years Spectroscopy Magazine has increased our coverage of artificial intelligence (AI), deep learning (DL), and machine learning (ML) and the mathematical approaches relevant to the AI topic. In this article we summarize AI coverage and provide the reference links for a series of selected articles specifically examining these subjects. The resources highlighted in this overview article include those from the Analytically Speaking podcasts, the Chemometrics in Spectroscopy column, and various feature articles and news stories published in Spectroscopy. Here, we provide active links to each of the full articles or podcasts resident on the Spectroscopy website.

Researchers from the University of Iceland and Matis Food and Biotech R&D in Reykjavík have unveiled an innovative study leveraging near-infrared (NIR) spectroscopy for real-time monitoring of fishmeal and oil processing. This advanced method promises to optimize product quality and streamline production, particularly in lipid composition and protein concentration—key markers for high-value fishmeal products.

Despite its widespread adoption in food quality analysis, near-infrared (NIR) spectroscopy lags behind in regulatory recognition. A study led by researchers from Italy and Spain highlights the disparity between its scientific applications and official methods, urging standardized regulations to fully leverage NIR's sustainability benefits.

Microplastics (MPs) and nanoplastics (NPs) are emerging contaminants requiring robust analytical techniques for identification and quantification in diverse environmental and biological matrices. This review highlights various spectroscopy methods, such as Raman, FT-IR, NIR, ICP-MS, Fluorescence, X-ray, and NMR detailing their methodologies, sample handling, and applications for characterizing MPs and NPs.

A novel method using fluorescence labeling and differential Raman spectroscopy claims to offer a more efficient, accurate approach to detect microplastics in seawater. Developed by researchers at the Ocean University of China, this method improves both the speed and precision of microplastic identification, addressing a key environmental issue affecting marine ecosystems.

Researchers from UCLA have developed a novel method to synthesize and stabilize anti-Bredt olefins (ABOs), defying long-held beliefs about their instability. This breakthrough, published in Science, paves the way for new applications in synthetic chemistry by leveraging the unique reactivity of these geometrically distorted molecules.

Researchers from the University of Cordoba have validated a novel spectroscopy technique to help distinguish between extra virgin and virgin olive oils. This approach could support existing panel-based tests, which are often slow, costly, and subjective, by providing a faster, non-destructive screening option.

A new review highlights the promising role of non-destructive spectroscopy techniques in enhancing olive and extra virgin olive oil (EVOO) quality assessments. By combining spectroscopy with imaging, researchers uncover innovative ways to determine product authenticity and improve quality control in olive oil production.

A leading-edge review highlights the potential of Raman spectroscopy for fast, non-invasive diagnostics in hematology and oncology. By mapping biochemical fingerprints, this technology could one day help detect cancers, monitor treatments, and even predict immune responses.

Recent research highlights the potential of infrared (IR) spectroscopy as a noninvasive diagnostic tool for cancer detection through blood derivatives. However, significant confounding factors pose challenges to its clinical adoption, necessitating rigorous standard operating procedures.

A team from Auburn University has developed an innovative ultrabroadband near-infrared (NIR) transient absorption (TA) spectrometer capable of detecting across a wide spectral range of 900–2350 nm in a single experiment. This advancement improves the study of ultrafast processes in low-bandgap materials and opens doors to new insights in photochemistry and charge dynamics.

A recent study showcases the potential of Fourier transform near-infrared (FT-NIR) spectroscopy and spatially offset Raman spectroscopy (SORS) in detecting raw material defects in hazelnuts caused by improper storage conditions. FT-NIR spectroscopy proved especially effective, while SORS offered complementary insights in certain scenarios. These spectroscopic methods could modernize the speed and accuracy of hazelnut inspections in the food industry.

A review by researchers from Curtin University comprehensively explores how chemometrics can revolutionize forensic science by offering objective and statistically validated methods to interpret evidence. The chemometrics approach seeks to enhance the accuracy and reliability of forensic analyses, mitigating human bias and improving courtroom confidence in forensic conclusions.

A new review highlights the use of ultraviolet–visible–near infrared (UV–vis–NIR) absorption spectroscopy in studying catalytic processes. The research discusses how this technique uncovers reaction mechanisms, structural properties, and reaction kinetics, particularly in heterogeneous and photocatalysis, and explores its potential for broader applications.

Hyperspectral imaging (HSI) is revolutionizing fields such as agriculture, food safety, and medical analysis by providing high-resolution spectral data. This emerging technology is proving invaluable in diverse applications, including plant stress detection, weed discrimination, and flood management. A new review explores HSI’s fundamental principles, applications, and future research directions.

Researchers from the University of Minho (Portugal) have developed a hyperspectral imaging database of human facial skin, aimed at improving various scientific applications such as psychophysics-based research and material modeling. The database includes 29 participants with diverse skin tones, providing detailed spectral reflectance data under controlled conditions.

This column is the continuation of our previous column that describes and explains some algorithms and data transforms beyond those most commonly used. We present and discuss algorithms that are rarely, if ever, seen or used in practice, despite that they have been proposed and described in the literature.