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The 20th European Winter Conference on Plasma Spectrochemistry (EWCPS 2025) is scheduled to take place from March 2 to 7, 2025, in Berlin, Germany. Here, we provide a conference insider regarding what spectroscopists should consider checking out, as well as the topics that will be discussed at the conference.

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At Pittcon this year, there will be numerous sessions dedicated to spotlighting the latest research that uses atomic spectroscopy or elemental analysis techniques. We highlight some of these talks below that might pique the interest of spectroscopists and researchers attending the conference this year.

By using a handheld NIR spectrometer, researchers aimed to optimize the classification process that makes it possible to differentiate between polyolefin and non-polyolefin films with a single measurement, even for thin films. Their findings could contribute to better recycling processes, helping to address the growing plastic waste problem. Spectroscopy spoke to Hana Stipanovic, corresponding author of a paper resulting from these efforts, about this research.

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.

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.

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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.

Microscope image of modified DNA strands displayed on advanced digital equipment in a biotech lab. Generated with AI. | Image Credit: © Sukifli.D - stock.adobe.com.

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.

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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.