Surface-Enhanced Raman Scattering on Ordered Metal Nanodot Array Obtained Using Anodic Porous Alumina
Bibliographic record
Abstract
The fabrication of an ordered array of Au nanodots using anodic porous alumina as an evaporation mask, and its application to a substrate for the measurement of surface-enhanced Raman scattering (SERS) were studied. One of the advantageous points of using anodic porous alumina as a template to fabricate nanostructures is that the size, shape and arrangement of the obtained nanostructures can be controlled by changing the geometrical structures of the porous alumina. Au nanodot arrays were obtained by thermal evaporation method. The SERS signals of pyridine molecules adsorbed on the nanodots were detected. The intensity of the SERS signals was strongly dependent on the arrangement of the nanodots. The enhancement factor of the intensity of the incident light on Au nanodots was analyzed by numerical calculations based on finite-difference time-domain (FDTD) method. The obtained SERS substrates are expected to be used for Raman spectra measurement with high sensitivity.
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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".