Infrared (IR) Spectroscopy

Chinese Academy of Sciences researchers combine spectroscopic methods with deep learning to classify microplastics at near-perfect accuracy.

A new study uses spectroscopic tools to analyze the spread and transformation of microplastics across water, soil, and air systems. Researchers also examined the limitations of global policies in addressing this multidimensional pollutant.

A new study by researchers from Spain and Brazil demonstrates that combining near- and mid-infrared spectroscopy with advanced statistical analysis can identify how growing site, harvest season, and clonal variation influence yerba mate’s chemical composition.

Researchers at the National Institute of Technology Rourkela have developed a highly accurate machine learning-assisted FT-IR spectroscopy method to detect and quantify sawdust adulteration in coriander powder, offering a fast and scalable solution to enhance food safety and authenticity.

A new study using infrared spectroscopy reveals that commercial beet sugar contains microplastic particles, raising concerns over food processing and packaging practices. Scientists identified various plastic types in sugar samples, including polyethylene and PET.

A recent study reveals that microplastics, primarily blue polyolefin fibers, are widespread throughout the western Arctic Ocean’s water column.

Algerian researchers used X-ray diffraction (XRD) with Rietveld refinement and Fourier transform infrared (FT-IR) spectroscopy to show how long-term exposure to desert conditions causes microstructural and compositional degradation in solar panels, offering critical insights for improving monocrystalline photovoltaic (PV) durability in extreme climates.

A recent study explored a new robust, multi-technique approach to detect ferric oxide red in spices.

A new study led by Gaëlle Belleau-Magnat at Université de Sherbrooke reveals that Arctic gossans, analyzed using rover-compatible techniques, may serve as valuable analogs for Martian environments and help guide the search for past life on Mars.

Mississippi State University researchers show that mid-infrared (MIR), a.k.a. infrared (IR), portable spectrometers, combined with calibration transfer techniques, can match lab instruments for soil property analysis.

Researchers at China Agricultural University developed a rapid and accurate spectroscopic method using NIR and FT-IR combined with PLS regression to measure protein content in rice noodles, enhancing quality control for the popular river snail rice noodle (luosifen) industry.

Spectroscopy's 2025 Emerging Leader in Molecular Spectroscopy is Lingyan Shi of the University of California, San Diego. Shi’s research focuses on developing and applying molecular imaging tools, including stimulated Raman scattering (SRS), multiphoton fluorescence (MPF), fluorescence lifetime imaging (FLIM), and second harmonic generation (SHG) microscopy.

This tutorial addresses the critical issue of analyte specificity in multivariate spectroscopy using the concept of Net Analyte Signal (NAS). NAS allows chemometricians to isolate the portion of the signal that is unique to the analyte of interest, thereby enhancing model interpretability and robustness in the presence of interfering species. While this tutorial introduces the foundational concepts for beginners, it also includes selected advanced topics to bridge toward expert-level applications and future research. The tutorial covers the mathematical foundation of NAS, its application in regression models like partial least squares (PLS), and emerging methods to optimize specificity and variable selection. Applications in pharmaceuticals, clinical diagnostics, and industrial process control are also discussed.

A new review article highlights the role Fourier transform infrared (FT-IR) spectroscopy plays in characterizing nanomaterials and polymers.

Researchers at the University of Belgrade have demonstrated that combining Raman and FT-IR spectroscopy with machine learning algorithms offers a highly accurate, non-destructive method for identifying seed varieties in lettuce, paprika, and tomato.

DOGE-related federal funding cuts have sharply reduced salaries, lab budgets, and graduate support in academia. Researchers view the politically driven shifts in priorities as part of recurring systemic issues in U.S. science funding during administrative transitions. The impact on Federal laboratories has varied, with some seeing immediate effects and others experiencing more gradual effects. In general, there is rising uncertainty over future appropriations. Sustainable recovery may require structural reforms, leaner administration, and stronger industry-academia collaboration. New commentary underscores similar challenges, noting scaled-back graduate admissions, spending freezes, and a pervasive sense of overwhelming stress among faculty, students, and staff. This article addresses these issues for the analytical chemistry community.

Top articles published this week include an interview series with Robert Ewing of the Pacific Northwest National Laboratory, a news article on using infrared (IR) cameras to see invisible methane leaks, and an article about the role of vibrational spectroscopy in analyzing plant-based food products.

Researchers in Scotland have developed a drone-mounted infrared imaging system that can detect and map methane gas leaks in real time from up to 13.6 meters away. The innovative approach combines laser spectroscopy with infrared imaging, offering a safer and more efficient tool for monitoring pipeline leaks and greenhouse gas emissions.

Researchers from institutions in Brazil harness near-infrared spectroscopy and machine learning to determine cocoa content with precision.

A new review highlights how vibrational spectroscopy techniques like FTIR, NIR, and Raman offer rapid, non-destructive tools for accurately analyzing plant-based protein content and structure.

Researchers at Xi’an Jiaotong University have demonstrated that ATR-FTIR spectroscopy, combined with histological analysis and machine learning, can accurately distinguish between drowning and strangulation in forensic cases.

A new review led by researchers from MIT and Oak Ridge National Laboratory outlines how artificial intelligence (AI) is transforming the study of molecular vibrations and phonons, making spectroscopic analysis faster, more accurate, and more accessible.

A recent study reports high-purity blue emission and thermal stability in novel lanthanum (III) complex synthesized via low-energy precipitation method.

This tutorial examines the modeling of diffuse reflectance (DR) in complex particulate samples, such as powders and granular solids. Traditional theoretical frameworks like empirical absorbance, Kubelka-Munk, radiative transfer theory (RTT), and the Hapke model are presented in standard and matrix notation where applicable. Their advantages and limitations are highlighted, particularly for heterogeneous particle size distributions and real-world variations in the optical properties of particulate samples. Hybrid and emerging computational strategies, including Monte Carlo methods, full-wave numerical solvers, and machine learning (ML) models, are evaluated for their potential to produce more generalizable prediction models.