Ultrasensitive nanoplasmonic biosensor based on interferometric excitation of multipolar plasmonic modes
Bibliographic record
Abstract
We propose a nanoplasmonic interferometric biosensor, which exploits the selective excitation of multipolar plasmonic modes in a nanoslit to provide a novel scheme for highly-sensitive biosensing. In this design, two counter-propagating surface plasmon polaritons interfere at the location of the nanoslit, selectively exciting the dipolar and quadrupolar modes of the structure depending on the phase relationship induced by the analyte. The contrasting radiation patterns produced by these modes result in large changes in the angular distribution of the transmitted light that depends on the analyte concentration. The resultant far-field is numerically modeled and the sensing performance of the structure is assessed, resulting in maximum bulk and surface sensitivities of S B = 1.12 × 10 5 deg/RIU and S S = 302 deg/RIU, respectively, and a bulk-sensing resolution of the order of 10 −8 RIU. The design allows ample control over the trade-off between operating range and resolution through the slit’s width, making this platform suitable for a broad range of sensing requirements.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".