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White Light Transmission Spectroscopy for Rapid Quality Control Imperfection Identification in Nanoimprinted Surface-Enhanced Raman Spectroscopy Substrates

2025· article· en· W4408071823 on OpenAlex
Mike Hardy, Hin On Chu, Serene Pauly, J. Wiggins, Alina Schilling, Pola Goldberg Oppenheimer, Liam M. Grover, R. J. Winfield, Jade N. Scott, Matthew D. Doherty, Ryan McCarron, William Hendren, P. Dawson, R. M. Bowman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueACS Measurement Science Au · 2025
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsnot available
FundersInnovate UKEngineering and Physical Sciences Research CouncilQueen's UniversityUniversity College CorkQueen's University BelfastUniversity of GlasgowUK Research and InnovationJames Watt School of Engineering, University of GlasgowWellcome Trust
KeywordsRaman spectroscopySurface-enhanced Raman spectroscopyMaterials scienceSpectroscopyNanoimprint lithographyPlasmonSubstrate (aquarium)NanotechnologyOpticsOptoelectronicsAnalytical Chemistry (journal)ChemistryRaman scatteringFabricationPhysics

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Miniaturized biomedical sensor development requires improvements in lithographic processes in terms of cost and scalability. Of particular promise is nanoimprint lithography (NIL), but this can suffer from a lack of high-fidelity pattern reproducibility between master and imprinted substrates. Herein, we present a multidisciplinary investigation into gold- and iron-coated NIL sensors including custom optics and spectroscopy, scanning probe microscopy, and data analysis insights. Polyurethane NIL-made nanodome arrays were interrogated with white light transmission spectroscopy, coupled with principal component analysis (PCA) to investigate potential offsets in the photon-substrate plane interaction angle, an imperfection in NIL substrates. Large-angle mismatches (2–10°) were found to be easily discernible by PCA with statistically significant differences ( p = 0.05). Unexpected dips in some spectra are postulated to be due to interacting localized and propagating plasmon polaritons, which is supported with a coupled two-oscillator model. General insights are made regarding the interpretation of PCA loadings, which should be related to physical phenomena, and where maximum variance is not necessarily the most meaningful criterion. Smaller angles (<1°) show no significant differences with overlapping confidence intervals in PCA space. Surface-enhanced Raman spectroscopy (SERS) measurements on gold-coated nanodomes returned relative standard deviations of 6–10% via analysis of gelatin, which is of interest as a nasal lining approximation. Interestingly, nanodomes coated in iron produced small, but useful SERS enhancements, which was subsequently interrogated via scanning thermal probe microscopy showing temperature increases of up to 5 °C over the area of one nanostructure (∼1 μm 2 ). Nanostructures remained intact despite the surprising large local temperature increase relative to a gold-coated comparison sample (∼2 °C). The current study provides a framework for the rapid and accurate quality control assessment of imperfections in NIL-produced nanostructures for sensing applications in SERS and surface plasmon resonance, which may need precisely fabricated nanostructures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.302
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it