Classification of Bacteria Using FT-IR

A new review led by researchers from MIT and Oak Ridge National Laboratory outlines how artificial intelligence (AI) is transforming the study of molecular vibrations and phonons, making spectroscopic analysis faster, more accurate, and more accessible.

An interview with Charles Wilkins, the winner of the 2013 American Chemical Society Division of Analytical Chemistry Award in Chemical Instrumentation, sponsored by the Dow Chemical Company.

This tutorial examines the modeling of diffuse reflectance (DR) in complex particulate samples, such as powders and granular solids. Traditional theoretical frameworks like empirical absorbance, Kubelka-Munk, radiative transfer theory (RTT), and the Hapke model are presented in standard and matrix notation where applicable. Their advantages and limitations are highlighted, particularly for heterogeneous particle size distributions and real-world variations in the optical properties of particulate samples. Hybrid and emerging computational strategies, including Monte Carlo methods, full-wave numerical solvers, and machine learning (ML) models, are evaluated for their potential to produce more generalizable prediction models.

Bernhard Lendl and Cosima Koch of the Vienna University of Technology have developed a new method for on-line monitoring of fermentations using mid-infrared spectroscopy.

A team of researchers from Spanish institutions has found that polystyrene used in healthcare packaging shows strong resistance to UVC sterilization, with minimal chemical degradation detected using FT-IR and Raman spectroscopy.