Surface-Enhanced Raman Scattering: Imaging and Mapping of Langmuir−Blodgett Monolayers Physically Adsorbed onto Silver Island Films
Bibliographic record
Abstract
The point-by-point mapping of the surface-enhanced resonance Raman scattering (SERRS) and surface-enhanced Raman scattering (SERS) spectra obtained from Langmuir−Blodgett (LB) monolayers of bis( n -butylimido)perylene (BuPTCD) on silver island films are reported. Wide field global images of the SERRS signal are also discussed. The mapping and global Raman images of the LB-coated silver surfaces, obtained using the 514.5 nm and the 780 nm laser lines, give a visual picture of the variation of the intensity of the SERRS/SERS signal on the rough metal surface with ca. 1 μm 2 spatial resolution. Neat and mixed LB monolayers of BuPTCD with arachidic acid of 20% and 1% molecular concentration of the analyte were used as samples in the SERRS and SERS experiments. This is the first report of SERS and SERRS mapping and imaging of single Langmuir−Blodgett monomolecular layers. The use of BuPTCD is particularly important, since the molecules are not chemically bound to the surface. SERRS spectra with large signal-to-noise ratio (100) are observed from a maximum of 40 000 molecules of the analyte with a collection time of 10 s.
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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".