All News


John Philip Walters (1)

John Philip Walters, Ph.D. (1938-2026), was an analytical chemist who spent 17 years researching the physics of spark-discharge emission spectroscopy at the University of Wisconsin-Madison before moving to St. Olaf College in 1982, where he became best known for pioneering a role-playing undergraduate laboratory model that had students take on professional roles to mirror real analytical-chemistry work. His 1991 three-part series on the approach in Analytical Chemistry earned him the ACS Division of Analytical Chemistry's J. Calvin Giddings Award in 1993, and he continued extending his understand-the-system teaching philosophy into computer-controlled instrumentation well into his later career.

Artist’s conception of a futuristic laser-based instrument ©  MD AL AMIN-chronicles-stock.adobe.com

Raman spectroscopy is shedding its bulky, benchtop reputation as chip-scale spectrometers, tip-enhanced probes, and AI-native detectors push the technique into pockets, production lines, and single molecules. The result is an instrument category being rebuilt from the optics up, faster, smaller, deeper, and smarter than the Raman systems of even five years ago.

Peter R. Griffiths, a pioneering figure in Fourier transform infrared (FT-IR) spectroscopy who authored or coauthored more than 300 scientific papers and numerous books over five decades, died August 29, 2026, at age 84. This tribute traces his career from Oxford and Digilab through Ohio University and the University of Idaho, his landmark books and the Handbook of Vibrational Spectroscopy, and his many honors, including the 2023 Ellis R. Lippincott Award and 2024 Optica Fellowship.

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.