Normal and Surface-Enhanced Raman Spectroscopy of Nitroazobenzene Submonolayers and Multilayers on Carbon and Silver Surfaces
Bibliographic record
Abstract
Raman and ultraviolet-visible (UV-Vis) absorption spectra were obtained for nitroazobenzene (NAB) chemisorbed on smooth and rough silver, and they were compared to published spectra for NAB on sp(2) hybridized pyrolyzed photoresist film (PPF) surfaces. High signal-to-noise ratio Raman spectra were obtained for 4.5 nm thick NAB films on PPF and smooth Ag due to significant enhancement of the NAB scattering relative to that observed in solution. The UV-Vis spectra of chemisorbed NAB exhibited a significant shift toward longer wavelength, thus bringing the NAB absorption closer to the 514.5 nm laser wavelength. The red shift was larger for PPF than for smooth Ag, consistent with the approximately 5x stronger Raman signal obtained on PPF. Deposition of Ag onto quartz without a chromium adhesion layer produced a rough Ag surface that enhanced the Raman spectrum of chemisorbed NAB by a factor of approximately 1000, as expected for roughened Ag due to electromagnetic field enhancement. The strong Raman signal permitted observation of NAB at low coverage and revealed changes in the NAB spectrum as the film progressed from submonolayer to multilayer thicknesses. Finally, deposition of Ag onto PPF/NAB samples through a metal grid produced Ag squares on top of the NAB, which enhanced the Raman scattering of the NAB layer by a factor of approximately 100. Deposition of a final conducting film on the Ag squares should permit in situ observation of a wide range of molecules in operating molecular electronic junctions.
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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".