UV-vis Spectroscopy

Researchers in Brazil have developed new optical techniques—SLIM, IC-scan, and RICO-scan—to probe the complex nonlinear properties of scattering and disordered materials, expanding potential applications in photonics, biomedicine, and thermometry.

Researchers have introduced a simple yet powerful new rule based on Rayleigh scattering theory that accurately links the absorption behavior of composite media, like aerosols or colloids, to the properties of their nanoparticle constituents.

In this tutorial, Thomas G. Mayerhöfer and Jürgen Popp introduce complex-valued chemometrics as a more physically grounded alternative to traditional intensity-based spectroscopy measurement methods. By incorporating both the real and imaginary parts of the complex refractive index of a sample, this approach preserves phase information and improves linearity with sample analyte concentration. The result is more robust and interpretable multivariate models, especially in systems affected by nonlinear effects or strong solvent and analyte interactions.

Researchers at Sun Yat-sen University have applied visible diffuse reflectance spectroscopy to reveal how iron oxide minerals, particularly hematite, define the iconic red hues of China's Danxia landforms.

Researchers from Northwestern University, University of Cádiz, and University of Arizona have developed new formulae for analyzing optical thin films that outperform traditional models by accounting for complex geometries and absorbing substrates. These advances offer more precise ultraviolet-visible-near-infrared (UV-vis-NIR) spectroscopic analysis of film materials used in critical modern technologies.

In this Icons of Spectroscopy article, Executive Editor Jerome Workman Jr. delves into the life and impact of Bruce Kowalski, an analytical chemist whose major contributions to chemometrics helped establish the field of applying advanced quantitative and qualitative mathematics to extract meaningful chemical information from complex datasets. Kowalski’s visionary approach to chemical data analysis, education, and software development has transformed the landscape of modern analytical chemistry for academia and industry.

Researchers in Rome used advanced spectroscopic techniques to probe the mineralogy of the CM2 carbonaceous chondrite NWA 12184. This revealed the effects of space weathering and provided insights into C-type asteroid evolution.

A newly published review in the journal Advanced Materials explores how intelligent wearable sensors, powered by smart materials and machine learning, are changing healthcare into a decentralized, personalized, and predictive modeling system. An international team of researchers highlights emerging technologies that promise earlier diagnosis, improved therapy, and continuous health monitoring—anytime, anywhere.

A study from Chinese researchers demonstrates how combining satellite imagery, land use data, and machine learning can improve pollution monitoring in fast-changing urban rivers. The study focuses on non-optically active pollutants in the Weihe River Basin and showcases promising results for remote, data-driven water quality assessments.

New research highlights how remote satellite sensing technologies are changing the way scientists monitor inland water quality, offering powerful tools for tracking pollutants, analyzing ecological health, and supporting environmental policies across the globe.

Modern remote sensing technologies have evolved from coarse-resolution multispectral sensors like MODIS and MERIS to high-resolution, multi-band systems such as Sentinel-2 MSI, Landsat OLI, and UAV-mounted spectrometers. These advancements provide greater spectral and spatial detail, enabling precise monitoring of environmental, agricultural, and land-use dynamics.

A global research team has detailed how smart sensors, artificial intelligence (AI), machine learning, and Internet of Things (IoT) technologies are transforming the detection and management of environmental pollutants. Their comprehensive review highlights how spectroscopy and sensor networks are now key tools in real-time pollution tracking.

A new study published in Spectrochimica Acta Part A by Dominik Heger and colleagues at Masaryk University reveals that phenol's photophysical properties change significantly when frozen, potentially enabling its breakdown by sunlight in icy environments.

On April 9th, Marama Labs, a scientific instrument company with offices in Wellington, New Zealand, and Dublin, Ireland, announced in a press release the launch of its new CloudSpec instrument.

A new study by researchers from Palo Alto Research Center (PARC, a Xerox Company) and LG Chem Power presents a novel method for real-time battery monitoring using embedded fiber-optic sensors. This approach enhances state-of-charge (SOC) and state-of-health (SOH) estimations, potentially improving the efficiency and lifespan of lithium-ion batteries in electric vehicles (xEVs).

A recent review in Energies explores the latest advancements in sensor applications for electric vehicle (EV) thermal management systems. The study, authored by Anyu Cheng, Yi Xin, Hang Wu, Lixin Yang, and Banghuai Deng from Chongqing University of Posts and Telecommunications, along with industry partners, examines how advanced optical sensors improve the efficiency, safety, and longevity of EVs.

A cutting-edge fiber optic sensing system, developed by researchers at Tongji University, leverages neural networks to classify vehicles with unprecedented accuracy. The system’s innovative design uses spectroscopic and optical sensor technologies to provide critical data for road maintenance and traffic management.

The second part of an in-depth interview exploring the use of flow imaging microscopy (FIM), a new technology used for subvisible particle characterization in biologics.

This study compares the sensitivity of CIE Lab values, peak area, and yellowness index for the determination of color attributes among a set of white and stained seashells exposed to tea tannins.

The first part of an in-depth interview exploring the use of flow imaging microscopy (FIM), a new technology used for subvisible particle characterization in biologics.

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.

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

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.

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.