Plasmonic nanostructure on a tapered fiber for chemical detection
Bibliographic record
Abstract
A simple, cost effective technique to manufacture plasmonic nanostructures as a Surface Enhanced Raman Spectroscopy (SERS) substrate was investigated. The plasmonic structure of gold nanorods was developed on the surface of a tapered fiber using the optical tweezing process from a colloidal solution. A unique grating like distribution of gold nanorods (GNRs) was formed. The effect of different laser wavelengths (632, 1064, and 1522 nm) on the assembly of the nanostructure was also investigated. The experiments were repeated with Gold nanospheres, which are referred to as gold nanoparticles (GNPs). However, no significant distribution of nanoparticles was observed. The tapered fiber was developed using dynamic and static chemical etching methods; a single-mode fiber (SMF 28), and a multimode fiber were used. The gold nanorods formed a grating like structure when optically tweezed using tapered multi-mode fiber. The potential use of the tapered fiber probe with nanostructure for application in SERS was investigated.
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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) | 0.001 | 0.001 |
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".