Exploring copper nanostructures as highly uniform and reproducible substrates for plasmon-enhanced fluorescence
Bibliographic record
Abstract
The unique properties of metallic nanostructures of coinage metals that can sustain localized surface plasmon resonances (LSPR) put them at the centre of plasmon-enhanced phenomena. The theory of plasmonic phenomena based on LSPR is well-established. However, the fabrication of plasmonic substrates, reproducibly, is still challenging for applications in surface-enhanced Raman scattering (SERS) and surface-enhanced fluorescence (SEF). In this work we describe well-ordered copper nanostructures (CuNSs), produced by electrodeposition and nanosphere lithography, as active substrates for SEF. After a detailed spectroscopic and microscopic characterization, CuNSs are successfully applied as SEF-active substrates using a well-known perylene derivative as a target molecule. The signal reproducibility from CuNS substrates was established by comparing the results against those obtained from a simply roughened Cu substrate. Under optimal conditions, signal variability is around 4%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".