On Wednesday, February 19th, 2025, from 8:30–9:30 am EST, a keynote address will take place at the American Academy of Forensic Sciences (AAFS) Conference. We preview the keynote here.

Spectroscopy sat down with Samiksha Singh to discuss her team’s latest research in microplastics research, which provided insight into how marine monitoring can improve mitigation of plastic pollution.

Scientists explore the potential of dilute III-V NIR semiconductors for Tuberculosis diagnostics, offering improved sensitivity and efficiency.

A joint study between the Institute for Environment and Energy, Technology and Analytics (IUTA e. V., Duisburg, Germany) and Heinrich Heine University Düsseldorf (Germany) explored the combination of size exclusion chromatography (SEC) with diode array detector (DAD) and capillary-enhanced Raman spectroscopy (CERS) to directly analyze hemolyzed serum samples. We spoke to Jana Thissen, first author of the paper resulting from this study, about her team’s work.

Researchers from Shandong University and the Chinese Academy of Sciences have developed the Shandong University Remote Raman Spectrometer (SDU-RRS), a remote Raman system designed to enhance mineral detection in planetary exploration.

W. W. Coblentz was one of the preeminent researchers in the field of infrared spectroscopy with work spanning a broad range of physics, chemistry, spectroscopic theory, instrumentation, applications, and sample handling. The Coblentz Society was established in his name in 1954 by Norman E. Wright and Van Zandt Williams.

Benjamin T. Manard has won the 2025 Emerging Leader in Atomic Spectroscopy Award for his pioneering research in nuclear material characterization and isotope ratio analysis, with expertise in advanced atomic spectrometry techniques such as inductively coupled plasma optical emission spectroscopy (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), and laser ablation.

Fourier transform infrared (FT-IR) microscopy using reflection methods (diffuse reflection, reflection/reflection-absorption, or attenuated total reflectance) typically requires less sample preparation than transmission. However, optimal results will depend upon the sample and, in particular, the sample surface.

This “Chemometrics in Spectroscopy” column traces the historical and technical development of these methods, emphasizing their application in calibrating spectrophotometers for predicting measured sample chemical or physical properties—particularly in near-infrared (NIR), infrared (IR), Raman, and atomic spectroscopy—and explores how AI and deep learning are reshaping the spectroscopic landscape.

Top articles published this week include an article celebrating women in spectroscopy, a video interview discussing how Raman microspectroscopy can help detect microplastics in potable water, and a news article about using attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy to detect fentanyl in fingernails.

In this column, I describe what I believe may be the origin of this fluorescence emission and support my conjecture with some measurements of polycyclic aromatic hydrocarbons (PAHs). Understanding the origin of these interfering backgrounds may enable you to design experiments with less interference, avoid the laser illuminations that make things worse, or both.

This year, the American Academy of Forensic Sciences Conference is taking place from February 17–22, 2025. We highlight the importance of spectroscopy in this field and why we’re covering the conference this year.

The study developed an effective mid-infrared spectroscopic identification model, combining principal component analysis (PCA) and support vector machine (SVM), to accurately determine the geographical origin of five types of millet with a recognition accuracy of up to 99.2% for the training set and 98.3% for the prediction set.

Researchers at Zhengzhou Police University have developed an AI-powered Raman spectroscopy method that achieves 100% accuracy in identifying plastic beverage bottles.

Researchers from Jiangsu University review advancements in computer vision and spectroscopy for non-destructive citrus quality assessment, highlighting the role of AI, automation, and portable spectrometers in improving efficiency, accuracy, and accessibility in the citrus industry.