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.
Spectroscopists are used to thinking about optimization. Every calibration model, every spectral fit, and every neural network is tuned against some objective, and anyone who has built a calibration model knows that it will faithfully minimize whatever function it is given, whether or not that function captures what actually matters. At
The day's program unfolded in two parts on Thursday, October 8, 2026. Kitt delivered the plenary lecture, "Why I Left Academia, and Why It Should Worry You: How academic science came to solve for the wrong objective, and what it costs to keep doing it," from 9:30 to 10:00 AM PDT in Sierra 5. That afternoon, the award session (AWD-Thu2: Emerging Leader Award) ran from 1:30 to 3:10 PM PDT in Cascade 1, with five 20-minute talks that showed the breadth of modern molecular spectroscopy, from single-molecule surface-enhanced Raman detection to the dye chemistry of centuries-old cloth.2
Presenter: Jay P. Kitt, PhD, MS, Director of Chemistry, Litmus Analytical, and Research Assistant Professor, University of Utah, Salt Lake City, Utah
Award lectures usually celebrate a body of research. Kitt chose a different path, using his plenary to examine the conditions under which research gets done, and why those conditions shaped his own decision to build his career in industry rather than on the tenure track (he keeps a research faculty appointment at the University of Utah).
He began by setting aside the threats to academic science that dominate hallway conversation: government shutdowns, shifting administrations, shrinking budgets, and, more recently, worries about automation and artificial intelligence. Those pressures are real, he acknowledged, but he argued that a less visible problem runs underneath them. As institutions came to depend more heavily on revenue, the practical goal of academic work drifted away from discovery, teaching, and solving real-world problems, and toward securing the money that funds them.
The framing will resonate with anyone who has built a chemometric model. In Kitt's telling, academic science has spent decades minimizing the wrong objective function. The algorithm is working as designed; the problem is what it was asked to optimize. He was careful to place the fault with the system rather than with the people in it. The field, he said, remains full of creative and capable scientists. What has changed is which behaviors the system selects for.
Kitt traced that drift through several observable outcomes. Grant success rates have fallen to levels that feel closer to chance than to merit. Published findings are reproduced less often than the community likes to acknowledge. A growing fraction of researchers leaves the tenure track each year, while the incentives that remain tend to favor safe, incremental projects over ambitious ones.
He argued that these costs are not abstract. He pointed to a field that initially rejected the work it would honor with a Nobel Prize decades later, to the author of a foundational discovery who had left research before that discovery was recognized, and to the many major recent advances that have emerged entirely outside academia. In his view, none of these outcomes is an accident. Each follows predictably from the objective the system has chosen.
The talk grew out of years of conversations with friends, colleagues, and senior faculty, some of whom had started their careers with considerably more optimism. Those discussions, Kitt explained, pushed him to look closely at the data while he weighed academia against industry, and the evidence brought him to a sobering conclusion. That analysis is also what led him to pursue research outside the university.
His closing concern was for the next generation. The objective a field optimizes is the one it teaches its students to pursue, and Kitt observed that early-career scientists are already questioning whether the price is worth paying. He left the audience with two questions: is this truly the function the community intends to keep minimizing, and how many talented people will it lose before it changes course?
If the plenary asked what science should optimize for, the afternoon session in Cascade 1 offered five examples of research aimed squarely at real problems: clinical detection, cultural heritage, food quality, pathogen safety, and energy and biosensing materials.
1:30–1:50 PM PDT | Presenter: Zac D. Schultz, PhD, The Ohio State University, Columbus, Ohio
Schultz opened the session with work on bringing surface-enhanced Raman spectroscopy (SERS) to flowing liquid samples. SERS pairs molecular specificity with exceptional sensitivity, which makes it attractive for tracking chemical signals and disease markers. Its path into clinical assays, however, has been slowed by persistent concerns about reproducibility and quantitation.
His group's answer is a sheath-flow SERS interface. Hydrodynamic focusing confines analyte molecules leaving a capillary into a narrow stream directly over a planar SERS substrate, where they are identified by their intrinsic Raman signatures. Because the detector sits at a capillary outlet, it couples naturally to capillary electrophoresis and high-performance liquid chromatography (HPLC) for post-separation identification. Schultz described recent studies of how analyte migration and sheath flow work together to improve detection, along with evidence that single molecules can be detected when their SERS cross sections are large. Chemical conjugation, he noted, can raise the cross section of weaker scatterers, opening a route to new diagnostic and prognostic assays.
1:50–2:10 PM PDT | Presenter: Caelin Celani, PhD, University of Delaware, Newark, Delaware | Co-authors: Ilaria Degano, PhD, Università di Pisa, Pisa, Italy; Karl S. Booksh, PhD, University of Delaware, Newark, Delaware | Project lead: Jocelyn Alcántara-García, University of Delaware, Newark, Delaware
Celani took the audience from the flow cell to the museum. HPLC remains the most chemically informative way to identify historical dyes, but it requires removing material from fragile objects that cannot be replaced. Fiber optic reflectance spectroscopy (FORS) is noninvasive, yet how much it can truly resolve has not been fully established.
The team tested FORS on 204 red Norwich textiles with well-documented provenance, combining cluster analysis, spectroscopic domain knowledge, and targeted HPLC confirmation. The near-infrared region added essentially nothing to sample discrimination. Instead, the visible region, and particularly 380–469 nm, drove the clustering among samples with HPLC-confirmed dye recipes. X-ray fluorescence (XRF) measurements showed that, except where the mordant was absent or below detection limits, a shift in the inflection point near 600 nm did not track mordant composition, pointing instead to the chromophores themselves.
Celani summarized three findings: FORS color information agrees reasonably well with HPLC-derived dye recipes; the approximately 600-nm shift is independent of mordant under the conditions studied; and many structure–spectrum relationships cited in the conservation literature are too weak in dyed textiles to support either multivariate discrimination or expert visual identification. That last point is a useful caution for anyone interpreting reflectance spectra of complex matrices.
2:10–2:30 PM PDT | Presenter: Jean-François Masson, PhD, Université de Montréal, Montreal, Quebec, Canada | Co-author: Saba Bashir, Université de Montréal
Masson brought a distinctly Canadian problem to Nevada. Grading maple syrup involves color class, flavor, and sugar profile, each typically judged by a separate analytical or sensory test, which creates a bottleneck for producers. His group asked whether a single Raman measurement could report on several quality attributes at once.
The study drew on more than 700 syrups spanning the golden, amber, dark, and very dark grades and several flavor categories. After preprocessing, principal component analysis (PCA) revealed spectral trends tied to color and flavor, but the groups overlapped considerably, suggesting that the link between Raman fingerprint and syrup character is too nonlinear for an unsupervised linear method to untangle. Convolutional neural networks trained directly on the spectra extracted those nonlinear features and improved discrimination. The work makes a compelling case for Raman spectroscopy as a multiparameter quality tool for complex food products.
2:30–2:50 PM PDT | Presenter: Marc D. Porter, PhD, University of Utah, Salt Lake City, Utah
Porter tackled a puzzle that has quietly troubled the immunoassay community. Several studies, including early work from his own laboratory, have reported detection limits at or below 1 colony-forming unit per milliliter (CFU/mL), lower than either the assay's intrinsic sensitivity or the tiny sample volumes involved could reasonably explain.
To find the source, his team examined immunoassays for Salmonella spp., Escherichia coli O157:H7, Mycobacterium avium subsp. paratuberculosis, and Bacillus globigii (now classified as Bacillus atrophaeus), a surrogate for B. anthracis, using high-resolution scanning electron microscopy and atomic force microscopy. They also compared results across laboratories and modeled signal generation from first principles. The answer was proteins shed from the microbial surface. These soluble antigens amplify the response well beyond what intact cells alone produce, meaning many assays measure both whole organisms and shed material. Combined with hypergeometric statistics describing the odds of actually capturing a whole organism in a small sample, the findings offer a more rigorous basis for defining and interpreting pathogen detection limits.
2:50–3:10 PM PDT | Presenter: Carol Korzeniewski, PhD, Texas Tech University, Lubbock, Texas
Korzeniewski closed the session with confocal Raman microscopy of materials operating on electrodes, including ionomers, redox polymers, conjugated organic polymers, and catalyst thin films. Her approach treats the confocal probe volume as a fixed reservoir: as a film swells or contracts with changes in hydration or redox state, the amount of material within that volume changes, and the Raman signal records it. A high-numerical-aperture oil-immersion objective provides tight focusing and efficient light collection.
She described volume-change measurements in ion-conducting membranes and redox polymers, then extended the method to organic mixed ionic–electronic conductors based on water-compatible 3-substituted polythiophenes, materials of interest for drug delivery and biosensing. Using multivariate analysis, her group followed the redox transformations that generate polaron and bipolaron states, and time-resolved spectra tracked how backbone and side-chain vibrational bands respond to a potential step or linear sweep.
Taken together, the plenary and the award session made for an unusually coherent day. Kitt's plenary challenged the audience to ask whether the scientific system is rewarding the right outcomes. The afternoon talks supplied a practical answer to what that work looks like when it is aimed at real problems: a SERS detector built for clinical reproducibility, a noninvasive method that spares irreplaceable artifacts, a single measurement that could streamline an agricultural industry, a hard look at what pathogen assays actually measure, and a window into polymers as they swell, shrink, and change charge state on an electrode.
Several threads ran across the session. Multivariate analysis and machine learning appeared in nearly every talk, from cluster analysis of textile spectra to convolutional networks for syrup grading. So did a healthy skepticism about what a signal really means, whether a reflectance inflection point, an ultralow detection limit, or an assumption inherited from the earlier literature. Fittingly, Porter's talk modeled the kind of rigor Kitt called for, revisiting results that looked too good to be true and asking why.
For early-career spectroscopists weighing their own paths, Kitt's message, delivered by a researcher who has moved his career into industry, may linger well beyond SciX 2026. His closing question deserves an answer from the whole community: if the objective function is wrong, who is responsible for changing it?
(1) Workman, J., Jr. The 2026 Emerging Leader in Molecular Spectroscopy Award. Spectroscopy 2026.
(2) SciX 2026 Full Schedule: Thursday, October 8, 2026. FACSS SciX 2026: The Great Scientific Exchange.
