Tip-enhanced Raman spectroscopy of graphene-like and graphitic platelets on ultraflat gold nanoplates
Bibliographic record
Abstract
In this study, tip-enhanced Raman spectroscopy (TERS) is used to characterize graphene-like and graphitic platelets composed of a few layers of graphene. Specifically, gap-mode TERS geometry provides a larger enhancement of the local electromagnetic field at the junction formed by a gold sharp tip and a gold substrate. Graphene-like platelets are deposited onto ultra-flat thin gold nanoplates using a surfactant-assisted method. Au-coated atomic force microscopy (AFM) tips are used to probe specific substrate regions coated by the platelets. TERS spectra are collected on distinctive points on the graphene-like layers and surrounding substrate using radially or linearly polarized light, with an excitation wavelength of 632.8 nm. The position, width and intensity of G, D, and 2D Raman-active modes of graphene are discussed as a function of the incident light polarization and for distinct positions on the graphene layer. We report here on the nature of the collected TERS spectra focusing in particular on the edges of the graphene platelets.
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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".