Real-time ultrasound sensing with a mode-optimized photonic crystal slab
Bibliographic record
Abstract
Integrated photonic sensors can provide large scale, flexible detection schemes. Photonic crystal slabs (PCSs) offer a miniaturized platform for wideband, sensitive ultrasound detection by exploiting the photoelastic effect in water. However, poor modal overlap with the sensing medium and non-negligible absorption loss of the aqueous medium have previously limited PCS sensor performance. In this study, we detail the development and optimization of a PCS-based acoustic sensor by adding to it a low-loss high-index polymer cladding layer. Exploiting a mode-optimized TM-like optical resonance present in a PCS, with high bulk index sensitivity ( >600nm/RIU ) and quality factor Q ( >8000 ), we demonstrate real-time ultrasound sensing at a noise equivalent pressure of 170 Pa ( 1.9Pa/Hz ). The PCS sensor is backside-coupled to an optical fiber, which, along with its intensity-based ultrasound-sensing architecture, will allow us to scale up easily to a 2D array. This work paves the way to a sensitive compact ultrasound detector for photoacoustic-based diagnostics and monitoring of tissue.
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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".