Statistical, Morphological, and Chemical Particle Characterization of Cellulose Nitrate Filters for QC

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.

An interview with Paul Pudney, a winner of the William F. Meggers Award.

Researchers from Northwest University in Xi’an, China, developed a novel portable Raman spectroscopy method with advanced chemometric techniques to accurately quantify harmful polycyclic aromatic hydrocarbons (PAHs) in oily sludge.

Volker Deckert, the winner of the 2013 Charles Mann Award, is advancing the use of tip enhanced Raman spectroscopy (TERS) to push the lateral resolution of vibrational spectroscopy well below the Abbe limit, to achieve single-molecule sensitivity. Because the tip can be moved with sub-nanometer precision, structural information with unmatched spatial resolution can be achieved without the need of specific labels.

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.