Jerome Workman, Jr.

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).

Researchers explore soft optical waveguides as a breakthrough technology for biocompatible sensing and robotics.

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 recent review published in Sensors explores the dynamic field of continuum robotics, with a particular focus on the advances in optical sensing technologies. The study, led by researchers from the Technical University of Košice and the University of Texas at Austin, highlights the dominance of optical fiber sensors in tracking robotic shape perception and environmental interactions, demonstrating spectroscopic applications and future potential.

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 research team from Nanjing University of Finance and Economics has developed a new analytical model using fluorescence spectroscopy and neural networks to improve the detection of aflatoxin B1 (AFB1) in vegetable oils. The model effectively restores AFB1’s intrinsic fluorescence by accounting for absorption and scattering interferences from oil matrices, enhancing the accuracy and efficiency for food safety testing.

A research team from Jiangsu University has developed a Raman spectroscopy-based method to detect aflatoxin B1 (AFB1) in peanuts with improved accuracy and efficiency. By employing a two-step hybrid strategy integrating backward interval partial least squares (BiPLS) and variable combination population analysis (VCPA), the new model significantly enhances the precision of AFB1 detection, providing a more reliable approach for food safety monitoring.

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.

In this Icons of Spectroscopy column, Executive Editor Jerome Workman Jr. delves into Part II of the Raman Effect, discovered by C. V. Raman, a physicist whose major contributions to vibrational spectroscopy have helped shape the field and advance one of the most important quantum-based spectroscopy tools of recent generations.

Researchers have developed a high-sensitivity optical fiber vibration sensor based on Fabry-Perot (F-P) interference, designed to improve wind turbine tower monitoring. This innovation addresses issues with traditional electrical sensors and has strong potential for integration into the Internet of Things (IoT) for real-time structural health monitoring.

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.

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.

In this "Icons of Spectroscopy" column, executive editor Jerome Workman Jr. delves into Part I of the life and work of C. V. Raman, a physicist who has made major contributions to the science of vibrational spectroscopy and created an understanding for one of the most important quantum-based spectroscopy tools in generations.

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.

Researchers have explored the Raman spectral properties of HgPSe3 thin flakes, revealing their structural uniformity and potential for high-performance ultraviolet-to-visible (UV-Vis) photodetectors. Their study, published in the Chinese Journal of Physics, highlights the material’s strong optoelectronic properties and fast response times.

Scientists explore the potential of dilute III-V NIR semiconductors for Tuberculosis diagnostics, offering improved sensitivity and efficiency.

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.

Benjamin T. Manard has won the 2025 Emerging Leader in Atomic Spectroscopy Award for his pioneering research in nuclear material characterization and isotope ratio analysis, with expertise in advanced atomic spectrometry techniques such as inductively coupled plasma optical emission spectroscopy (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), and laser ablation.

This “Chemometrics in Spectroscopy” column traces the historical and technical development of these methods, emphasizing their application in calibrating spectrophotometers for predicting measured sample chemical or physical properties—particularly in near-infrared (NIR), infrared (IR), Raman, and atomic spectroscopy—and explores how AI and deep learning are reshaping the spectroscopic landscape.