Nanoscopic imaging of oxidized graphene monolayer using tip-enhanced Raman scattering
Bibliographic record
Abstract
Tip-enhanced Raman scattering (TERS) can be used for the structural and chemical characterization of materials with a nanoscale resolution, and offers numerous advantages compared to other forms of imaging. We use TERS to track the local structural features of a CVD-grown graphene monolayer. Ag nanoparticles were added to AFM probes using ion-beam sputtering in order to make them TERS-active. Such modification provides probes with large factors of enhancement and good reproducibility. TERS measurements on graphene show an emergence of a defect-induced D-Raman band and a strain-induced shoulder of the graphene’s G-band. Comparison of TERS results with micro-Raman for oxidized graphene suggests that local oxidation occurs with the introduction of sp3 defects, under TERS conditions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".