Data Analytics, Statistics, Chemometrics, and Artificial Intelligence

The 2026 first edition of Spectroscopy's Chemometrics, Data Processing, Machine Learning, and Artificial Intelligence Terminology Guide defines the classical chemometric, statistical, machine learning, AI, and process analytical technology (PAT) terms most likely to be encountered by working spectroscopists, analytical chemists, and process engineers.

Near-infrared spectroscopy combined with principal components analysis and a back propagation neural network identified Huanglongbing-infected Gannan navel orange leaves with an overall accuracy of 98.75%, outperforming LDA, KNN, and SVM models.

Atomic spectroscopy has quietly gone from counting elements in bulk to counting single nanoparticles, imaging tissue at the micrometer scale, and reading Martian rocks from several meters away. The instruments got smaller, the software got smarter, and the questions they can now answer got a lot more interesting.

UV–vis absorption spectroscopy, one of analytical chemistry's oldest and most accessible techniques, remains foundational to cutting-edge science, underpinning the Nobel Prize-winning discovery and synthesis of quantum dots and continuing to evolve through ultralow stray-light optics, chip-scale sensors, and AI-integrated process analyzers.

The following articles are the most accessed digital object identifier (DOI) manuscripts for Spectroscopy and LCGC International during the month of September 2026. Nine articles are individually ranked here by DOI page views; the third-highest entry (186 views) was recorded against the bare journal-level DOI rather than an individual article and is therefore not attributable to a single manuscript.

Near-infrared (NIR) spectroscopy, built on the weak overtone and combination-band absorptions first exploited commercially in the 1970s, is now being reshaped by chip-scale MEMS sensors, rapid field calibration methods, and increasingly capable chemometric and machine-learning models.

SciX 2026, the annual conference presented by the Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), ran October 4–9, 2026, at the Nugget Casino Resort in Sparks, Nevada. The program spanned atomic and molecular spectroscopy, mass spectrometry, chemometrics, and bioanalysis. This report follows the meeting day by day, from Monday's clinical Raman plenaries to Friday's closing talks, drawing on the online program and Spectroscopy coverage of award winners, highlighting efforts to move Raman, SERS, LIBS, and single-particle ICP-MS toward clinical, environmental, and field use.

Four finalists for the FACSS Innovation Award presented on the afternoon of October 8, 2026, at SciX 2026. Their work spanned drone-mounted laser-induced breakdown spectroscopy (LIBS), a touch-and-sound virtual reality system for blind scientists, polarized infrared (IR) imaging of shape memory polymers, and an ultrasound-activated plasmonic nanoplatform aimed at Parkinson’s disease.

At SciX 2026, Thursday morning’s “New Challenges in Chemometrics” session questioned long-held assumptions, from reliance on autonomous model selection to the restriction of spectral data to real numbers.

A candid plenary on the incentives shaping academic science was followed by an afternoon of talks spanning flowing SERS detection, historical textiles, maple syrup, pathogen immunoassays, and electrochemical Raman microscopy.

Wednesday's program at SciX 2026 kept returning to one question: can spectroscopy perform outside the controlled laboratory? Speakers took surface-enhanced Raman scattering (SERS), laser-induced breakdown spectroscopy (LIBS), mid-infrared photonics, chemometrics, and fluorescence excitation–emission matrix (EEM) spectroscopy into clinics, food plants, reactor coolant loops, brine fields, and drinking water supplies.

Near-infrared spectroscopy has quietly stopped being a niche calibration exercise and started acting like an autonomous diagnostic partner, reading consciousness in an injured brain, steering a fermenter without a human hand, and hunting invisible plastic in a glass of water. The tool chemists once used to check moisture in grain is now fusing with artificial intelligence to make decisions no spectrometer could make alone.

FT-IR spectroscopy, long treated as a mature bench technique for confirming a carbonyl stretch or fingerprinting a polymer, has quietly become one of chemistry’s most versatile discovery engines: it now infers molecular structure straight from a spectrum without a reference library, resolves chemistry tens of nanometers wide, and screens a fingerstick of blood for disease in minutes. The last five years of published research show FT-IR moving from a confirmatory tool into a predictive, autonomous, and field-ready analytical platform.

Raman spectroscopy is entering one of its most consequential periods since its commercialization, driven by artificial intelligence, coherent heterodyne detection, and radical instrument miniaturization, with new deep-learning frameworks and portable systems moving Raman analysis into fields, factories, and crime scenes.

In this Q&A overview, we explore the derivation of principal component analysis using elementary algebra rather than standard matrix notation.

A new review article in Microchimica Acta finds that smartphone-based optical and spectroscopic sensors show strong potential to decentralize food safety testing across contaminants like pesticides, heavy metals, and pathogens.

Raman spectroscopy just got a brain, a stopwatch, and a nose. Together, these upgrades are turning a century-old light-scattering trick into a frontline tool for catching cancer earlier, chiral drugs cleaner, and toxic chemicals faster than ever before.

The following articles are the most accessed digital object identifier (DOI) manuscripts for Spectroscopy and LCGC International during the month of August 2026. Ten articles are individually ranked here by DOI page views.

The bulky bench-top NIR spectrometer is quietly being dismantled and rebuilt as a wafer-scale photonic chip, a self-calibrating algorithm, and a sensor small enough to ride in a shirt pocket. What once demanded a grating, a moving mirror, and a climate-controlled lab now fits inside a handheld module, a bioreactor probe, or a drone payload, and it increasingly figures out what it is looking at on its own.

Reliability, dynamic measurements, artificial intelligence, and real-world applications are reshaping Raman spectroscopy – while Molecular Photonics points toward new translational frontiers.

Jurgen Popp, Thomas Mayerhofer, and colleagues at Leibniz IPHT and Friedrich Schiller University Jena introduce the Personalized Optical Digital Twin (PODT), a Photonics21 contribution to Europe's Virtual Human Twin ecosystem that connects molecular photonics—Raman blood analysis, coherent Raman tissue imaging, and multimodal endomicroscopy—with longitudinal physiology and clinical data. Drawing on the published multicenter INTELLIGENCE trials, the authors argue that technical feasibility and clinical utility must be evaluated separately as the field moves toward Europe's FP10 research agenda.

A proof-of-concept study combines a convolutional neural network feature extractor with the conventional hit quality index (HQI) to improve Raman spectral comparison, reducing spurious similarity and improving discrimination between closely related protein and antibody spectra.

The nomination deadline for the 2027 EAS Chemometrics Award, which recognizes significant and lasting contributions to chemometrics, has been extended to September 15, 2026.

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.

A history of the James L. Waters Symposium at Pittcon, from its 1987 origins and its founder, instrument entrepreneur James Logan Waters, through thirty-six installments of speakers spanning gas chromatography to generative AI.