Atomic Spectroscopy

In this video segment, Sarah Theiner dives into the research that she conducted at the University of Vienna, which focused on how chemoresistance affects drug distribution in the tumor microenvironment.

In this interview clip, we turn the focus to the advent of artificial intelligence (AI) and machine learning (ML) in spectroscopy, and Alex Scheeline discusses how AI and ML will enhance SIBS and LIBS calibration.

In this video segment, Martin Resano of the University of Zaragoza talks about the challenges and advancements in obtaining isotopic information using atomic spectroscopy.

The 2026 James L. Waters Annual Symposium at Pittcon will focus on the integration of generative AI into analytical chemistry, examining how large language models and AI tools can support method development, data analysis, and chemical measurement while maintaining scientific rigor, validation, and interpretability. Continuing its decades-long tradition of connecting historical perspective with emerging technologies, the symposium will feature presentations from leading chemists and spectroscopists, highlighting both the opportunities and challenges of responsibly incorporating AI into chemical measurement science.

Artificial intelligence is transforming vibrational spectroscopy by automating calibration, feature extraction, and interpretation across Raman, infrared, near-infrared (NIR), and hyperspectral imaging (HSI) systems. This review of articles highlighted in Spectroscopy during 2025 captures several major developments, spanning data fusion, spectral imaging, and industrial and biomedical applications.

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

A recent study demonstrated that deep learning combined with ICP spectroscopy can accurately and affordably predict multiple soil properties.

The article highlights how rapidly advancing, non-destructive spectroscopic and imaging technologies, supported by AI, multi-modal data integration, and increasing instrument portability.

This first article in a two-part series introduces the foundations and terminology of AI as applied to chemometrics, defines key algorithmic approaches, and explores their growing role in spectral data analysis, model quantitative calibration, classification, and interpretability.

Here are ten main unsolved problems in vibrational and atomic spectroscopy, each accompanied by a tutorial-style synopsis suitable for advanced practitioners or graduate-level students. Each of these tutorials, spanning advanced spectroscopy modeling, chemometrics, machine learning (ML) interpretability, and standardization, consists of a descriptive article. Each piece is well-referenced (with detailed matrix equations, radiative transfer models, chemometric derivations, and so forth), and includes the following. • Special focus on each topic—including mathematical derivations in matrix notation. • Conservative, verifiable content anchored to established reference sources. • Appropriate tutorial article structure: Title, Summary, Abstract, Introduction, Theory with equations, Examples, Discussion & Future Research, and References.

James Dudley Winefordner was a preeminent figure in analytical chemistry whose contributions to spectrochemical method development, instrumentation, and mentoring shaped generations of scientists.

This tutorial explains how baseline drift and multiplicative scatter distort spectroscopic data, reviews correction techniques such as MSC, SNV, EMSC, wavelet-based detrending, and AsLS baseline estimation with matrix-based derivations, and explores emerging data-driven scatter modeling strategies and future research directions.

A recent review by Jhonatan Contreras and Thomas Bocklitz from Friedrich Schiller University Jena and the Leibniz Institute of Photonic Technology delves into the emerging field of explainable artificial intelligence (XAI) in spectroscopy.

This tutorial examines the development of universal spectral libraries, reviewing standardization efforts, mathematical frameworks, and practical examples across multiple spectroscopies, while emphasizing metadata harmonization, FAIR principles, and the emerging role of AI in building interoperable, machine-readable repositories. This remains an unsolved problem in spectroscopy.

This tutorial explores the challenges posed by nonlinearities in spectroscopic calibration models, including physical origins, detection strategies, and correction approaches. Linear regression methods such as partial least squares (PLS) dominate chemometrics, but real-world data often violate linear assumptions due to Beer–Lambert law deviations, scattering, and instrumental artifacts. We examine extensions beyond linearity, including polynomial regression, kernel partial least squares (K-PLS), Gaussian process regression (GPR), and artificial neural networks (ANNs). Equations are provided in full matrix notation for clarity. Practical applications across near-infrared (NIR), mid-infrared (MIR), Raman, and atomic spectroscopies are discussed, and future research directions are outlined with emphasis on hybrid models that integrate physical and statistical knowledge.

This tutorial explores the motivation, mathematical underpinnings, and practical approaches to fusing spectral data, with emphasis on early, intermediate, and late fusion strategies.

This Icons of Spectroscopy article profiles Lester W. Strock, whose innovative research in crystal chemistry and spectroscopy bridged fundamental science and applied geochemistry.

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.

Researchers at China’s National Key Laboratory have identified 170 nickel autoionization states using resonance ionization mass spectrometry, significantly advancing the spectral database critical for laser isotope separation and atomic spectroscopy.

Researchers from Nanjing University of Information Science & Technology have introduced a breakthrough AI-enhanced multimodal strategy for real-time detection of polyamide microplastics contaminated with heavy metals.

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.

Tue, Jul 15, 2025 1:00 PM EDT

This study used three distinct sample preparation techniques to examine the metal content of geological rocks.

Webinar Date/Time: Wednesday, July 23rd, 2025 Morning Session: 11:00 am EDT - 1:00 pm EDT Afternoon Session: 2:00 pm EDT - 3:00 pm EDT Thursday, July 24th, 2025 Morning Session: 11:00 am EDT - 1:00 pm EDT Afternoon Session: 2:00 pm EDT - 3:00 pm EDT

Wednesday, June 25, 2025 at 11 am PST | 2 pm EST