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Oh, the Places We Went! Top Spectroscopy Conferences and Insights from 2025

AI Developments That Changed Vibrational Spectroscopy in 2025

ABB to Develop Infrared Spectrometer Concept for Canada’s Lunar Rover Mission

Bioimpedance Spectroscopy Emerges as a New Tool for Produce Quality Assessment

How Will Spectroscopy Benefit From Data-Driven Approaches?

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Top articles published this week include a farewell address from associate editorial director Caroline Hroncich, a new column on carbonyl compounds from Brian Smith, and an inside look at A-TEEM spectroscopy.

A heartfelt farewell reflecting on the meaningful work, community, and accomplishments achieved during my time at Spectroscopy.

In a recent press release, Renishaw unveils TRRS technology, revolutionizing Raman spectroscopy by overcoming fluorescence challenges for accurate analysis of complex samples.

A study published in the Journal of Raman Spectroscopy reports the detection of polyethylene, PET, and nylon microplastics in Greece’s remote Dragon Lake on Mt. Tymfi.

In this "Molecular Spectroscopy Workbench" column, a new spectroscopy, called A-TEEM, is explored.

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.

Discover how LIBS revolutionizes forensic science by enabling rapid, precise bone identification, overcoming challenges of traditional methods with advanced AI classification.

Spectroscopy is rapidly evolving, and professionals who build expertise in AI-driven analytics, automation, and high-demand sectors like pharma, biotech, and materials science will be best positioned to advance their careers despite industry-wide talent and budget challenges.

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. Breakthroughs in spectrum-to-structure models, machine learning (ML)-accelerated molecular dynamics, and field-deployable classic Raman, near-infrared (NIR), and surface-enhanced Raman spectroscopy (SERS) sensors pushed vibrational techniques from complex laboratory characterization toward automated structure elucidation, rapid analysis, and real-world sample sensing (1–6,9). This summary article highlights key 2025 contributions and their implications for the year of discovery.

A recent study provides a detailed introduction to uniform manifold approximation and projection (UMAP) for analyzing LA-ICP-TOF-MS data. By converting high-dimensional MSI data into two-dimensional spaces, UMAP facilitates automated visualization to identify spectral clusters. Spectroscopy spoke to the paper’s lead author, Katharina Kronenberg of the University of Graz, about her group’s work.

A proposed update to United States Pharmacopoeia (USP) <1029> was published in July 2025 for industry comment. What’s changed and are the changes significant?

Top articles published this week include interviews with Paolo Oliveri of the University of Genoa (Italy) and Maryam Shakiba and Santiago Marin of the University of Colorado Boulder, and an inside look at vibrational spectroscopy trends.

Discover a cost-effective method for analyzing electrolyte elements in sports drinks using microwave plasma atomic emission spectroscopy, enhancing quality control and accuracy.

A new study from Heilongjiang Bayi Agricultural University introduces a high-accuracy, explainable deep learning model that significantly improves nondestructive nitrogen and chlorophyll estimation in maize canopies using hyperspectral data.

























