Jerome Workman, Jr.

Jerome Workman, Jr.

Jerome Workman, Jr. is former Senior Technical Editor of LCGC. He is on the Editorial Advisory Board of Spectroscopy and is the current Assoc. Editorial Director. He is the co-host of the Analytically Speaking podcast and has published multiple reference text volumes, including the three-volume Academic Press Handbook of Organic Compounds, the five-volume The Concise Handbook of Analytical Spectroscopy, the 2nd edition of Practical Guide and Spectral Atlas for Interpretive Near-Infrared Spectroscopy, the 2nd edition of Chemometrics in Spectroscopy, and the 4th edition of The Handbook of Near-Infrared Analysis. He is the recipient of the 2020 NY/NJ SAS Gold Medal Award (with Howard L. Mark). Mark and Workman have written over 250 Statistics and Chemometrics columns for Spectroscopy. Direct correspondence to [email protected]

Articles by Jerome Workman, Jr.

Atomic spectroscopy has quietly moved past splitting light and counting ions toward instruments that track a single nanoparticle, fuse a laser pulse with an isotope-ratio mass spectrometer, and correct their own interferences with artificial intelligence in real time. The result is a new class of ICP-MS, LIBS, and X-ray fluorescence (XRF) platforms that are turning what used to be a benchtop-only science into field-ready, self-optimizing analytical intelligence.

This is Chemometrics in Spectroscopy Column Number 251. In Column Number 250, we left you with a puzzle. We had just shown that a little-known piece of two-hundred-year-old mathematics, Lagrange's method of undetermined multipliers, could force an MLR calibration to ignore one particular, carefully chosen direction of repack-induced spectral change. It worked, but it only handled one direction at a time, and we admitted we had no idea whether the trick could be extended to PCR or PLS. That bothered us. So in this installment we go looking for the more general version of the idea, and we find it sitting in some very good recent work by Neal Gallagher and Nathanial Watson on what they call clutter suppression (a framework built for a completely different problem, target detection in hyperspectral imaging, that turns out to fit ours almost perfectly). Put the two together and you get an algorithm that whitens the calibration spectra with a clutter covariance matrix estimated from repack replicates, then hands the whitened data to the same Lagrangian machine we built last time. The payoff: the correction now generalizes to several, non-proportional directions of diffuse-reflection variability at once, and, because it is just a preprocessing step, it works ahead of PLS and PCR as well as MLR, which finally answers the question we could not answer before. This approach may very well be an answer to repack variation in repeated solid or slurry sample measurements using diffuse reflection. In this column we change gears with our writing tone and format by taking a "chemometry" approach, rather than a strict tutorial one. In future columns we hope to "unpack" this information in our more typical extended and tutorial manner. Let's explore solving this repack variation problem together.

Spectroscopy Top 10 DOI Articles of the Month (July 2026)

Spectroscopy Top 10 Articles of the Month (July 2026)

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The following articles are the most accessed digital object identifier (DOI) manuscripts for Spectroscopy and LCGC International during the month of July 2026. Nine articles are ranked here by DOI page views; a tenth entry in the July report (135 views) was recorded against the bare journal-level DOI rather than an individual article and is therefore not attributable to a single manuscript.

Refraction of Light Through a Solid © Graphicazzy -chronicles-stock.adobe.com

For 170 years, spectroscopists have built quantitative analysis on only one number pulled from every spectrum they ever recorded, discarding its inseparable twin. New dispersion-theory and complex-valued chemometric methods recover that missing half, the refractive index, and in favorable systems cut calibration error by as much as an order of magnitude.

Traditional Blood Glucose Meter © pittawut -chronicles-stock.adobe.com

Nearly every diabetic on earth still stabs a finger to measure their blood sugar, but a small army of lasers, infrared beams, and machine-learning algorithms is quietly plotting to end that ritual for good. This review tracks the photons chasing glucose through skin, from near-infrared reflectance to Raman fingerprints, and asks why the “needle-free” promise keeps slipping just out of reach.

Close up of artist’s rendition of a handheld spectrometer ©  whitestorm -chronicles-stock.adobe.com

Spectrometers that once filled an entire lab bench now fit in a coat pocket, and they are quietly reshaping how fentanyl gets identified on a roadside, how counterfeit cashmere gets caught on a loading dock, and how a five-hundred-year-old painting gets authenticated without ever leaving the wall. This review tracks five years of coverage from Spectroscopy alongside the broader literature to show how handheld Raman, FT-IR, NIR, and XRF instruments moved from laboratory novelty to field necessity.

United States White House with Waving American Flag ©  Bijac -chronicles-stock.adobe.com

A rule proposed by the White House Office of Management and Budget (OMB) would give political appointees final authority over discretionary grant decisions ahead of peer reviewers, allow agencies to terminate active grants without a formal right of appeal, and restrict international collaboration and publication funding across federal science agencies. For the optical, molecular, vibrational, and atomic spectroscopy community, the proposal could affect the grants, journal support, and student and postdoctoral positions that sustain the field.

Pine Forest During Rainstorm Lush Trees | Image Credit: © Lane Erickson - stock.adobe.com

This review highlights major advances in infrared (IR) and near-infrared (NIR) spectroscopy from 2022–2026, including instrument miniaturization, hyperspectral imaging, machine learning, and artificial intelligence. These developments are expanding the use of vibrational spectroscopy beyond the laboratory into portable and field-deployable analytical systems. Environmental applications such as microplastic detection, biosolids analysis, soil characterization, and contaminant monitoring are emerging as key growth areas.

Gold Anniversary Candles: Our 250th Article on Statistics, Chemometrics, and AI in over 40 years! ©  Valerii Evlakhov -chronicles-stock.adobe.com

In their milestone 250th column, Howard Mark and Jerome Workman, Jr. describe a mathematically rigorous algorithm that minimizes or eliminates sampling repack variation in near-infrared spectroscopy. The method separates systematic spectral changes caused by sample rearrangement from true compositional information, enabling more robust calibration models and significantly improving analytical repeatability for powdered and heterogeneous solid samples.

Research Profiles in Spectroscopy

This first installment of Research Profiles in Spectroscopy Series features The University of California, Santa Barbara (UCSB) Petrochronology Research Group and its advances in laser ablation ICP-MS, isotope geochemistry, and petrochronology. Led by John Cottle, Andrew Kylander-Clark, and Morgan Adamson, the group has developed innovative spectroscopic methods that combine high-resolution isotopic dating with trace-element analysis to better understand petrochronology processes, including mountain building, crustal evolution, and complex geological processes.

Most Influential Articles in Spectroscopy Series

This new feature in Spectroscopy introduces a structured, application-focused series that curates and examines the most influential research papers in molecular and atomic spectroscopy. Each installment presents a focused “Top 10” collection of seminal publications within a specific analytical domain, spanning techniques such as ultraviolet–visible, infrared, Raman, near-infrared, and atomic spectroscopy. Across biomedical, biopharmaceutical, environmental, and forensic applications, the selected papers illustrate how spectroscopic methods are applied to real-world analytical challenges. Emphasis is placed on the integration of spectral data with chemometric approaches to enable robust calibration, accurate prediction, and meaningful interpretation. Together, these curated collections provide practitioners with a concise, application-oriented perspective on impactful developments in spectroscopy. This article brings together the first nine “Top 10” collections in the series, offering a cross-disciplinary view of influential work shaping the field.

New product in the hands of a businessman. | Image Credit: © natali_mis - stock.adobe.com

Spectroscopy is rapidly evolving into an integrated, intelligent ecosystem where advances in instrumentation, detectors, and optics—combined with chemometrics and artificial intelligence (AI)—are enabling higher sensitivity, miniaturization, multimodal analysis, and real-time decision-making across techniques ranging from ultraviolet–visible (UV–vis), infrared (IR), and Raman to inductively coupled plasma mass spectrometry (ICP-MS), laser-induced breakdown spectroscopy (LIBS), and X-ray fluorescence (XRF). Together, these developments are driving automation, predictive modeling, and the emergence of autonomous analytical laboratories with increasingly connected, cloud-enabled workflows.

Two people wearing protective suits working at crime scene evaluating evidence © Seventyfour -chronicles-stock.adobe.com

Over the past two years, molecular spectroscopy has undergone a marked transformation from a predominantly laboratory-based analytical approach into a field-deployable, data-rich forensic toolkit. This evolution has been driven by three converging trends: (i) advances in vibrational spectroscopic instrumentation (Fourier transform infrared [FT-IR], Raman, and near-infrared [NIR], (ii) the integration of chemometrics and machine learning for extracting actionable information from complex spectra, and (iii) the emergence of portable and miniaturized devices suitable for in situ analysis. The ten papers reviewed here collectively demonstrate how spectroscopy is now addressing some of the most persistent challenges in forensic science—such as time since deposition (TSD), post-mortem interval (PMI), trace evidence discrimination, and rapid drug identification—while maintaining evidentiary integrity through non-destructive analysis. Importantly, these works also reflect a shift toward interpretability, validation, and legal defensibility, which are essential for courtroom acceptance.

The 2026 LCGC Lifetime Achievement and Emerging Leader in Chromatography Awards Session (AI Generated).

At Pittcon 2026 in San Antonio, Texas, the LCGC International Awards Session was held on Tuesday, March 10, from 1:30 PM to 4:40 PM. This session, presided by Jerome Workman, Jr., celebrated two distinguished scientists whose work has significantly influenced modern separation science. This annual session honors both a lifetime of achievement and the promise of emerging leadership in chromatography. In its nineteenth year, the program recognized Jack Henion with the LCGC Lifetime Achievement Award and Bob W. J. Pirok with the LCGC Emerging Leader in Chromatography Award.

Pittcon 2026: San Antonio Texas skyline and River Walk ©  Shaon -chronicles-stock.adobe.com

The Pittcon (Pittsburgh) Conference and Expo in San Antonio featured a forward-looking symposium exploring how generative artificial intelligence (AI) may transform the daily practice of analytical chemistry. The James L. Waters Symposium, “Generative AI in the Analytical Chemist’s Toolbox for Chemical Measurements”, took place on Monday, March 9, 2026 (2:30–4:40 p.m.) in Room 221A. The session was presided over by Daniel W. Armstrong of The University of Texas at Arlington, who introduced the topic by emphasizing the rapidly expanding knowledge base required of modern analytical chemists. In addition to chemistry, today’s analytical scientist must command elements of physics, advanced mathematics, data science, and, increasingly, AI. The symposium focused on the practical integration of generative AI tools into chemical measurement science. Speakers discussed how AI can assist analytical chemists with tasks such as algorithm generation, signal processing, literature synthesis, and data interpretation. Importantly, the session emphasized responsible implementation, highlighting the need for rigorous validation, high-quality data sets, and integration into existing laboratory workflows.