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In this edition of “Inside the Laboratory,” Dr. Bryan Eigenbrodt of Villanova University, in Villanova, Pennsylvania, discusses his laboratory’s work using operando spectroscopic techniques to better understand the chemistry occurring in alternative energy fuel cell devices such as solid oxide fuel cells (SOFCs).

A Researcher from Lomonosov Moscow State University has developed a convolutional neural network (CNN) model for Fourier transform infrared (FT-IR) spectra recognition. This AI-based system is capable of classifying 17 functional groups and 72 coupling oscillations with remarkable accuracy, providing a significant boost to material analysis in fields like organic chemistry, materials science, and biology.

Noureddine Melikechi Image Credit: ©Courtesy of Melikechi

Using logistics regression on laser-induced breakdown spectroscopy (LIBS) spectra of plasma samples collected pre- and post- Covid-19 pandemic from donors known to have developed various levels of antibodies to the SARS-Cov-2 virus, University of Massachusetts physics professor Nourddine Melikechi’s research team has shown that relying on the levels of sodium (Na), potassium (K), and magnesium (Mg) together is more efficient at differentiating the two types of plasma samples than any single blood metal alone. We spoke to Melikechi about this research.