Infrared (IR) Spectroscopy

A new review article systematically compared ammonia monitoring technologies and measurement protocols in pig production, offering a practical decision-support framework to guide researchers, farmers, and policymakers toward reliable, regulation-ready emission monitoring.

Artificial intelligence is transforming vibrational spectroscopy by automating calibration, feature extraction, and interpretation across Raman, infrared, near-infrared (NIR), and hyperspectral imaging (HSI) systems. This review of articles highlighted in Spectroscopy during 2025 captures several major developments, spanning data fusion, spectral imaging, and industrial and biomedical applications.

ABB announced that they will develop a lunar soil analysis instrument for Canada's Lunar Utility Rover, enhancing lunar exploration and resource utilization through advanced infrared spectroscopy.

A recent study from researchers in Indonesia and Taiwan demonstrates that tourism intensity on Gili Trawangan Island is strongly linked to higher microplastic contamination in coastal waters, sediments, and fish, highlighting the need for targeted waste management and sustainable tourism policies to protect vulnerable island ecosystems.

In this part of our ongoing review of the infrared spectra of carbonyl-containing functional groups, we will study the spectra of esters and carbonates. Esters are ubiquitous in our food and medicines, and polymeric carbonates form an important part of the materials around us. As always, concepts will be illustrated with reference spectra.

In 2025, the vibrational-spectroscopy community saw a convergence of deep learning, advanced simulation, and portable instrumentation that materially changed how spectra are interpreted and applied.

Vibrational spectroscopy is undergoing a major transformation driven by advances in new AI and machine learning, portable instrumentation, nanofabrication, hyperspectral imaging, and robust chemometrics. These developments are enabling more sensitive measurements, field-deployable analysis, multimodal data fusion, and automated spectral interpretation suitable for real-world industrial and clinical use. As these technologies converge, the field is positioned for a renaissance that may redefine how spectroscopy is practiced by 2030.

This review article highlights how a new review by Da-Wen Sun demonstrates that integrating spectroscopy with chemometric techniques can significantly improve cold chain food quality monitoring, authentication, and overall system efficiency.

The study reveals that infrared and Raman spectroscopy can accurately identify dye sources and detect light-induced chemical degradation in culturally significant Māori harakeke fibers.

A new review by researchers from the University of Waterloo, Sanofi, and McGill University highlights how vibrational and fluorescence spectroscopy are reshaping real-time monitoring of pharmaceutical bioprocesses. The authors detail recent advances in UV-Vis, NIR-MIR, Raman, and fluorescence sensing, supported by modern chemometrics and AI tools.

This mini-tutorial explores how data preprocessing (DP) transforms raw FT-IR ATR spectra into meaningful, reliable inputs for chemometric modeling. Readers will learn about key DP methods: normalization, scatter correction, centering, scaling, and baseline correction, and how proper selection of these techniques improves accuracy, reproducibility, and interpretability in infrared spectroscopic analysis.

Fourier transform infrared (FT-IR) spectroscopy is a versatile, non-destructive analytical tool used to characterize molecular structures, monitor chemical reactions, and quantify analytes in diverse materials. This mini-tutorial reviews fundamental principles, key operational modes, and practical examples across environmental, biomedical, and industrial applications. Readers will review and learn how to optimize FT-IR methods, interpret spectra, and avoid common pitfalls in data collection and processing.

In this continuation of our discussion with Sergei Kazarian and Bernadette Byrne, they address how recent advancements in FT-IR imaging are set to propel the biomedical and pharmaceutical industries forward.

Webinar Date/Time: Tue, Dec 9, 2025 10:00 AM EST

A recent study explores how Fourier transform infrared (FT-IR) spectroscopy can be used to predict key dough-making characteristics.

Spectroscopy sat down with Sergei Kazarian and Bernadette Byrne to talk about their latest research collaboration, which offers insights into why FT-IR spectroscopic imaging is advantageous in biomedical and pharmaceutical analysis.

This video in the Icons of Spectroscopy series highlights the life and scientific achievements of Albert A. Michelson, the first American Nobel Laureate in the sciences. It traces his journey from his early years in the American West and his education at the U.S. Naval Academy to his groundbreaking experiments measuring the speed of light. We explore his invention of the Michelson interferometer, its role in the famous Michelson–Morley experiment, and its lasting influence on modern optical and spectroscopic methods, including astronomy.

The miniaturization of spectroscopic instruments has reached a remarkable milestone: wearable vibrational spectroscopy. Techniques such as Raman, surface-enhanced Raman scattering (SERS), infrared (IR), and functional near-infrared (fNIRS) spectroscopy are no longer confined to the laboratory bench—they now fit on our bodies, into household devices, and onto industrial equipment. These wearable devices promise continuous, real-time monitoring, offering molecular-level insights for personal health, household management, clinical care, and industrial applications.

This second part of the Recent Research in Chemometrics and AI for Spectroscopy article surveys current and emerging applications of artificial intelligence (AI) in spectroscopy, highlighting explainable AI (XAI), deep learning, and generative AI frameworks.

This first article in a two-part series introduces the foundations and terminology of AI as applied to chemometrics, defines key algorithmic approaches, and explores their growing role in spectral data analysis, model quantitative calibration, classification, and interpretability.

Researchers uncover the hidden dangers of ship paint-derived microplastics, revealing their complex composition and ecological risks in marine environments.

Here are ten main unsolved problems in vibrational and atomic spectroscopy, each accompanied by a tutorial-style synopsis suitable for advanced practitioners or graduate-level students. Each of these tutorials, spanning advanced spectroscopy modeling, chemometrics, machine learning (ML) interpretability, and standardization, consists of a descriptive article. Each piece is well-referenced (with detailed matrix equations, radiative transfer models, chemometric derivations, and so forth), and includes the following. • Special focus on each topic—including mathematical derivations in matrix notation. • Conservative, verifiable content anchored to established reference sources. • Appropriate tutorial article structure: Title, Summary, Abstract, Introduction, Theory with equations, Examples, Discussion & Future Research, and References.

A new study reveals that resveratrol binds to peanut protein arachin through hydrophobic and hydrogen-bond interactions, enhancing protein stability and offering valuable insights for developing functional peanut-based food products.

This curated collection of recent Spectroscopy magazine mini-tutorials highlights the latest analytical and data-driven innovations in vibrational spectroscopy. Covering NIR, Raman, O-PTIR, and related optical methods, the series emphasizes practical workflows, emerging machine learning integrations, and advanced chemometric techniques for real-world laboratory applications—from food and environmental monitoring to biomedical analysis and nanoscale imaging.

A new perspective from researchers at the Karlsruhe Institute of Technology explores the evolving relationship between human expertise and artificial intelligence in polymer chemistry.