Influence of Losses, Device Size, and Mode Confinement on Integrated Micro-Ring Resonator Performance for Absorption Spectroscopy Using Evanescent Field Sensing
Bibliographic record
Abstract
This work presents a detailed modeling-based analysis of integrated micro-ring resonators used for absorption spectroscopy. Generally, sensors based on micro-ring resonators detect changes in the real part of the sensing medium refractive index, at critical coupling. In absorption spectroscopy, however, micro-ring resonators are used to measure changes in the imaginary part of the index and are most sensitive away from critical coupling, with separate maxima in the under- and over-coupled regimes. In this work, we present a detailed analysis of the under-coupled regime, explaining the relationships between sensitivity, mode confinement, and losses. The analysis is based on reverse-symmetry waveguides to increase the proportion of mode power in the sensing medium and incorporates a realistic model of propagation losses based on experimental measurements of sidewall roughness. The analysis demonstrates that the resonant nature of the sensor is most effective at small radii compared to a non-resonant structure of equal size and shows a behavior of diminishing returns at larger device sizes regarding sensitivity and elevated proportions of mode power in the evanescent field.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".