Dendritic Plasmonics for Mid-Infrared Spectroscopy
Bibliographic record
Abstract
Metallic nanostructures that exhibit tailored optical resonances spanning from the near to mid-infrared spectral range are of particular interest for spectroscopic and optical measurements in these spectral domains that can benefit from localized surface-enhancement effects. Plasmon resonances shifted in the near or mid-infrared range could be used to further enhance the excitation and/or the emission of an optical process. Surface-enhanced infrared absorption (SEIRA) is one of such processes and can particularly benefit from plasmon-enhanced local fields yielding an increase in sensitivity toward the detection of an analyte. Herein, we have fabricated a series of gold dendritic nanostructures, prepared by electron-beam lithography, that exhibit plasmon resonances spanning the near and mid-infrared spectral regions. We explore the influence of the number of branches of the dendritic structures as well as the length of each generation together with the overall effect of the shape and symmetry on the resulting optical resonances. The creation of new resonances that appear upon newer fractal generation is explained in light of an hybridization model. Selected structures were then evaluated for SEIRA measurements toward an analyte.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".