High optical enhancement in Au/Ag alloys and porous Au using Surface-Enhanced Raman spectroscopy technique
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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 (SnO 2 :F) substrate by laser fluency equal to 0.5 J/cm 2 or 1.0 J/cm 2 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 it