Infrared (IR) Spectroscopy

Drawing from Brian C. Smith’s “IR Spectral Interpretation” column, this Q&A article explores the unique characteristics, definitions, and spectral signatures of inorganic compounds.

For Pittcon 2026, the James L. Waters Symposium, scheduled for Monday, March 9, from 2:30 to 4:40 p.m. in Room 221A, turns its focus on Generative artificial intelligence (AI) systems in analytical chemistry, which are increasingly being used for analytical data interpretation, algorithm development, experimental planning, and scientific communication. This article introduces the general concepts of generative AI and its use in spectroscopy.

The 2026 James L. Waters Annual Symposium at Pittcon will focus on the integration of generative AI into analytical chemistry, examining how large language models and AI tools can support method development, data analysis, and chemical measurement while maintaining scientific rigor, validation, and interpretability. Continuing its decades-long tradition of connecting historical perspective with emerging technologies, the symposium will feature presentations from leading chemists and spectroscopists, highlighting both the opportunities and challenges of responsibly incorporating AI into chemical measurement science.

Pittcon 2026 will take place March 9–11, 2026, in San Antonio, Texas, building on the 2025 conference’s emphasis on eco-friendly practices and serving as the premier global event in analytical research, scientific instrumentation, and applied spectroscopy. An opening plenary session, “Spectroscopy and Sustainability: A Perfect Match,” will highlight how advances in spectroscopic technologies—from biomedical and pharmaceutical applications to UAV-based hyperspectral imaging, CBRNE detection, hazardous materials monitoring, and even extraterrestrial studies—are driving sustainable solutions across diverse fields.

A recent study demonstrated that hyperspectral imaging offers a highly accurate, dramatically faster alternative to traditional FT-IR methods for identifying microplastics in the Po River.

Researchers at Washington State University Tri-Cities demonstrate that combining Raman and infrared spectroscopy with convolutional neural networks enables highly accurate, low-cost, and field-ready automated plastic identification.

A recent review article explored methods that are used in agriculture to detect ammonia in pig housing. In the second part of our discussion of this topic, we focus on the protocols and frameworks and their importance in measuring ammonia in pig production.

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.

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.