Infrared (IR) Spectroscopy

Researchers from the Institute of Nuclear Physics Polish Academy of Sciences have unveiled new insights into the molecular arrangement of the 7HH6 compound’s smectic phases using X-ray diffraction (XRD) and infrared (IR) spectroscopy.

In a recent study published in Marine Pollution Bulletin, a team of researchers from several Spain and Portugal universities and institutions (Rovira i Virgili University, Universitat de Barcelona, University of Porto, and Institut d'Investigació Sanitaria Pere Virgili (IISPV) assessed microplastic (MP) contamination along the Mediterranean coastline.

Recent advancements in exoplanet detection, including high-resolution spectroscopy, adaptive optics, and artificial intelligence (AI)-driven data analysis, are significantly improving our ability to identify and study distant planets. These developments mark a turning point in the search for habitable worlds beyond our solar system.

Scientists are using advanced spectroscopic techniques to probe the universe, uncovering vital insights about celestial objects. A new study by Diriba Gonfa Tolasa of Assosa University, Ethiopia, highlights how atomic and molecular physics contribute to astrophysical discoveries, shaping our understanding of stars, galaxies, and even the possibility of extraterrestrial life.

Astronomers have made a significant leap in the study of exoplanet atmospheres with a new ground-based spectroscopic technique that rivals space-based observations in precision. Using the Exoplanet Transmission Spectroscopy Imager (ETSI) at McDonald Observatory in Texas, researchers have analyzed 21 exoplanet atmospheres, demonstrating that ground-based telescopes can now provide cost-effective reconnaissance for future high-precision studies with facilities like the James Webb Space Telescope (JWST) (1-3).

Top articles published this week include some of our columns in the most recent Spectroscopy magazine issue as well as more coverage from the American Academy of Forensic Sciences (AAFS) Conference.

In the fifth installment of “The Big Review” of infrared (IR) spectral interpretation, we review the spectroscopy of functional groups containing C-O bonds, discuss alcohols and phenols, and see how to use IR spectroscopy to distinguish these alcohols from each other. We then discuss ethers and see how to use IR spectroscopy to distinguish the three different types from each other.

In this "Icons of Spectroscopy" column, executive editor Jerome Workman Jr. details how Tomas B. Hirschfeld has made many significant contributions to vibrational spectroscopy and has inspired and mentored many leading scientists of the past several decades.

A study published in the International Journal of Dairy Technology by lead author Mark A. Fenelon and his team at Teagasc Food Research Centre and University College Dublin demonstrates that ATR-FT-IR spectroscopy can effectively monitor heat-induced structural changes in milk proteins and colloidal calcium phosphate, offering valuable insights for optimizing dairy product stability and quality.

Researchers at Oregon State University explore how machine learning, optical sensors, and robotics are transforming food quality assessment and processing, improving efficiency and reducing waste.

Given the importance of this nomenclature in guiding authors and reviewers, we invite members of the spectroscopy community to provide feedback, suggest updates, or participate in future revisions.

A new study published in the Journal of Dairy Science demonstrates that FT-MIR spectroscopy can effectively authenticate farming practices and dairy systems in Parmigiano Reggiano production but has limited ability to verify animal welfare parameters.

Researchers have developed a portable mid-infrared (IR) spectroscopic method combined with chemometric analysis to rapidly and non-destructively detect aflatoxin contamination in Aspergillus-infected peanuts. This approach offers a field-deployable alternative to traditional wet chemistry methods, with high sensitivity and specificity in identifying toxic metabolites such as aflatoxins.

University of Granada researchers compared different methods and their effectiveness in classifying ink found in historical documents.

A new approach to analyzing bituminous coals was created using Fourier transform infrared spectroscopy.

A study by researchers at Universidad de Talca in Chile explores the integration of artificial intelligence (AI), the Internet of Things (IoT), and remote sensing to modernize modern farming. The research highlights how these technologies optimize resource use, improve crop yields, and promote sustainable agricultural practices.

With Pittcon 2025 officially beginning, here are some notable upcoming workshops based around the advancement of spectroscopy.

A recent review by researchers at Nagpur University and Seth Kesarimal Porwal College explores the ever advancing landscape of the Internet of Things (IoT) and its essential components—sensors and actuators. The review paper classifies various IoT sensors and examines their role in integrating the physical and digital worlds to enable smarter devices and enhanced automation.

Our IR Spectral Interpretation column contains some of the most popular articles, according to our readers.

This article highlights key contributors who have significantly advanced the field of spectroscopy in recent decades.

A team of researchers from the International Iberian Nanotechnology Laboratory (INL) in Braga, Portugal, has developed an autonomous Internet of Things (IoT) spectral sensing system designed to monitor grape ripening in real-time. The study, led by Hugo M. Oliveira, Alessio Tugnolo, Natacha Fontes, Carlos Marques, and Álvaro Geraldes, was published in Computers and Electronics in Agriculture and introduces a novel approach to non-destructive, in-situ optical monitoring of grape maturity.

A new study examines the role of Internet of Things (IoT) technology in fostering sustainable urban development. Through a systematic review of 73 publications, researchers highlight how IoT-enabled sensors improve air quality, transportation, disaster management, and resource efficiency in smart cities.

The most viewed Spectroscopy DOI-registered articles from January 2025.

Researchers highlight the growing role of Internet of Things (IoT) and sensor technologies in enhancing food security and agricultural sustainability. The study, published in Ain Shams Engineering Journal, explores the applications, benefits, and challenges of smart agriculture, emphasizing the potential of optical sensors in monitoring and optimizing farming practices.

A recent study provides an in-depth overview of the latest advancements in infrared (IR) semiconductor sensor technology, highlighting new materials, enhanced detection capabilities, and expanding applications across industrial, medical, security, and environmental fields. The research explores how quantum dots, graphene, and novel nanomaterials are revolutionizing IR detection, paving the way for more efficient and versatile sensor systems.

Spectroscopy sat down with Samiksha Singh to discuss her team’s latest research in microplastics research, which provided insight into how marine monitoring can improve mitigation of plastic pollution.

W. W. Coblentz was one of the preeminent researchers in the field of infrared spectroscopy with work spanning a broad range of physics, chemistry, spectroscopic theory, instrumentation, applications, and sample handling. The Coblentz Society was established in his name in 1954 by Norman E. Wright and Van Zandt Williams.

Fourier transform infrared (FT-IR) microscopy using reflection methods (diffuse reflection, reflection/reflection-absorption, or attenuated total reflectance) typically requires less sample preparation than transmission. However, optimal results will depend upon the sample and, in particular, the sample surface.

The study developed an effective mid-infrared spectroscopic identification model, combining principal component analysis (PCA) and support vector machine (SVM), to accurately determine the geographical origin of five types of millet with a recognition accuracy of up to 99.2% for the training set and 98.3% for the prediction set.