Near-field chemical mapping of gold nanostructures using a functionalized scanning probe
Bibliographic record
Abstract
We report on photochemical and photophysical properties produced by Surface Plasmon Resonance (SPR) on metallic nanograins by means of high resolution Functionalized Tip-Enhanced Raman Spectroscopy (F-TERS). This technique relies on a sharp gold tip functionalized with Raman-active molecules to be scanned relatively to plasmonic hot-spots on a surface. We describe the local variation of plasmon-induced Raman enhancement on the surface of nanostructures that also affects the photochemistry while the quantitative interpretation of peak intensities requires the consideration of surface topography near the tip apex. Our F-TERS maps show Raman modes of hot electron reduction of 4-nitrothiophenol (4-NTP) molecules on the tip and indicate at least partial photochemical dimerization. An apparent photo-induced reversibility of this dimerization can be conservatively explained by a local topography feature that we simulate in a finite element environment. Our experimental results reveal a spatial resolution of approximately 10 nm, corresponding to a few hundred 4-NTP molecules exposed to the near-field.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".