Highlights from What’s Nu September 2026

The foundational theme of Volume 19 of Spectroscopy’s “What's Nu” LinkedIn newsletter is how fundamental concepts like Feynman’s path-integral formulation connect to vibrational spectra, while showcasing Raman spectroscopy's expansion into field tools, indoor aerosol tracking, and optical digital twins.

In the following Q&A, we provide an overview of what the latest “What’s Nu” covered, which includes new research in environmental analysis and clinical analysis.

How does the newsletter connect Richard Feynman’s 20th-century quantum mechanics to modern vibrational spectroscopy?

At the beginning of the newsletter, “What’s Nu” discussed Richard Feynman’s 1948 path-integral formulation, which calculates quantum events by summing contributions across all possible paths between two points.¹ Because molecular vibrations represent quantum nuclear motion on potential energy surfaces, path-integral methods provide a crucial mathematical framework for computational spectroscopy.^1–4 They allow researchers to model systems where classical molecular dynamics fail, including strongly anharmonic vibrations, light nuclei like hydrogen, zero-point motion, and far-infrared spectra of liquid water and helium.^1–4 The article also notes Feynman’s 1965 Nobel Prize in Physics for quantum electrodynamics (QED). In his Nobel lecture, Feynman cited Willis Lamb's experimental measurements of the Lamb shift in hydrogen, illustrating how precision spectroscopy was essential in testing and refining QED.^2–4

In "Beyond the Fingerprint," how has Raman spectroscopy overcome traditional limits to become a field-ready tool?

In the article, associate editorial director Jerome Workman Jr. outlined how advances in timing, artificial intelligence (AI), materials, and optics are overcoming long-standing Raman limitations. For example, to suppress signal-drowning fluorescence, Renishaw’s picosecond time-resolved detection uses single-photon avalanche diode arrays to isolate early Raman photons, while Tsinghua University's dual-wavelength Raman cancels tissue fluorescence to detect early esophageal cancer markers.⁵ Computational deep-learning models (like Vib2Mol) translate vibrational spectra into molecular structures, while neural networks classify foodborne pathogen serotypes with 98.4% accuracy and screen blood plasma for lung cancer with an AUC of 0.94.⁵ Nanostructured gold nanorods in ZIF-8 nanoparticles enable SERS to distinguish mirror-image chiral amino acid enantiomers like D- and L-valine.⁵ Additionally, density functional theory (DFT) databases distinguish 40 PFAS "forever chemical" isomers, and multipass cavities boost signals a thousandfold to detect methane down to 0.12 ppm.⁵

What insights does Purdue’s Brandon Boor share regarding indoor nanoscale aerosol measurement in his Q&A?

In Part 1 of a three-part Q&A expanding on his American Chemical Society (ACS) Fall 2026 presentation, Dr. Brandon Boor discusses measuring indoor airborne nanoparticles in the 1–3 nm nanocluster regime. His team combines field campaigns in Purdue facilities with controlled experiments in the full-scale zEDGE residential test house. The zEDGE test house allows prescribed routines (cooking, cleaning) under controlled ventilation, enabling mass-balance modeling to determine emission rates.⁶ To capture ultrafine 1–3 nm nanoclusters, Boor and his team used a particle size magnifier–scanning mobility particle sizer (PSMPS).⁶ This device works by allowing particles to pass through a bipolar charger (Kr-85 or soft X-ray) to reach a predictable charge distribution.⁶

A differential mobility analyzer uses concentric electrodes up to 10 kV to classify particles by electrical mobility trajectory.⁶ Classified nanoclusters undergo two-stage vapor growth using diethylene glycol and butanol before optical laser counting.⁶

What is the Personalized Optical Digital Twin (PODT), and what lessons emerged from its clinical trials?

Jürgen Popp and colleagues proposed the Personalized Optical Digital Twin (PODT) as a Photonics21 contribution to Europe's Virtual Human Twin (VHT) ecosystem. PODT connects molecular photonics, including Raman leukocyte phenotyping, coherent anti-Stokes Raman scattering (CARS) histology, and endomicroscopy, with wearable physiological tracking, clinical history, and AI.⁷ The issue details the multicenter INTELLIGENCE trials, which evaluated high-throughput Raman leukocyte phenotyping across 279 patients in six centers.⁷ Measuring ~1,500 leukocytes per patient within one hour proved operational feasibility in routine laboratory settings.⁷ However, the Raman score added no significant diagnostic value to combined clinical ICU/ED models.⁷ This underscores that technical feasibility and clinical decision utility must be evaluated separately as research moves toward Europe’s FP10 agenda.

References

1. Feynman, R. P. Space-Time Approach to Non-Relativistic Quantum Mechanics. Rev. Mod. Phys. 1948, 20, 367–387. DOI: https://doi.org/10.1103/RevModPhys.20.367
2. Poulsen, J. A.; Nyman, G.; Rossky, P. J. Feynman–Kleinert Linearized Path Integral (FK-LPI) Algorithms for Quantum Molecular Dynamics, with Application to Water and He(4). J. Chem. Theory Comput. 2006, 2, 1482–1491. DOI: https://doi.org/10.1021/ct600167s
3. Shepherd, S.; Lan, J.; Wilkins, D. M.; Kapil, V. Efficient Quantum Vibrational Spectroscopy of Water with High-Order Path Integrals: From Bulk to Interfaces. J. Phys. Chem. Lett. 2021, 12, 9108–9114. DOI: https://doi.org/10.1021/acs.jpclett.1c02574
4. Feynman, R. P. The Development of the Space-Time View of Quantum Electrodynamics. Nobel Lecture, December 11, 1965. Nobel Prize—Feynman’s 1965 Nobel Lecture.
5. Workman, Jr., J. Beyond the Fingerprint: How Raman Spectroscopy Learned to See Through Noise, Disease, and Deception. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/beyond-the-fingerprint-how-raman-spectroscopy-learned-to-see-through-noise-disease-and-deception (accessed September 28, 2026).
6. Boor, B. E.; Wetzel, W. Sizing Up the Nanoscale: Measuring Nanocluster Aerosol in Indoor Air. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/sizing-up-the-nanoscale-measuring-nanocluster-aerosol-in-indoor-air (accessed September 28, 2026).
7. Popp, J.; Mayerhöfer, T. G.; Borowsky, A.; Schmitt, M.; Meier-Ewert, L.; Hamm, G. From Molecular Snapshots to Longitudinal Prevention: The Personalized Optical Digital Twin. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/from-molecular-snapshots-to-longitudinal-prevention-the-personalized-optical-digital-twin (accessed September 28, 2026).