High optical enhancement in Au/Ag alloys and porous Au using Surface-Enhanced Raman spectroscopy technique
Bibliographic record
Abstract
Abstract We report high optical enhancement in Ag/Au alloys and porous gold nanostructures using Surface Enhanced Raman Spectroscopy (SERS) technique. Scanning electron microscopy investigation shows the formation of Ag/Au alloys particles during irradiation of Ag–Au bilayer deposited on FTO (SnO2:F) substrate by laser fluency equal to 0.5 J/cm2 or 1.0 J/cm2 with 12 ns laser pulse duration. The dealloying process of these Au–Ag alloy particles leads to the formation of Au nanoporous particles. The obtained nanostructures were studied with SERS and revealed a promising enhancement factor in porous Au nanostructure and tunability of localized surface plasmon resonance. The highly dense strong hot spots and large specific area in porous structure of gold nanostructures is the origin of the highly enhancement factor observed experimentally and theoretically. A very good agreement between simulation and experimental results was found confirming the potential of Au/Ag alloys and particularly porous gold nanostructure in SERS application.
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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) | 0.000 | 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 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".