Self-referencing surface plasmon sensor for resolution enhancement
Bibliographic record
Abstract
In this paper, a self-referencing evanescent field sensor based on surface plasmon resonances is designed and fabricated. The sensor is based on sub-wavelength two-dimensional gold gratings and is optimized to detect changes in the surrounding refractive index for a water-like material. The sensor has a dedicated mode for self-referencing, which is isolated from the surrounding environment and can be used to correct errors due to temperature variations. To understand the important design parameters and optimize the sensor for best performance, many variations were fabricated and measured experimentally. Using a localized surface plasmon resonance dominant mode, a high sensitivity of 435 nm/RIU was achieved experimentally, while the self-referencing mode was successfully isolated from the surrounding environment within a refractive index range of 1.34 to 1.39. Further, we show that by incorporating the self-referencing mode into the sensitivity measurements, the resolution of the sensor can be improved by a factor of 3.6. This approach can be employed effectively for resolution enhancement of the plasmonic sensors in the presence of environmental variations.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".