A practical Tamm plasmon sensor based on porous Si
Bibliographic record
Abstract
We report the fabrication and characterization of a new type of porous Si sensor using the Tamm plasmon resonance. The sensor consists of a photonic crystal created by periodic electrochemical anodization of crystalline Si, followed by partial thermal oxidation. The photonic crystal is transferred to a Au-coated glass substrate to allow optical measurements of surface modes at the metal/porous Si interface. This configuration greatly simplifies sensing since an analyte can be introduced in the pores from the opposite side of the metal layer without disrupting the optical path. The fabricated device exhibits a Tamm plasmon resonance within the photonic bandgap at a wavelength of 794 nm with a quality factor of 25. We observe a wavelength shift of the resonance when the nanosized pores are infiltrated with different concentrations of a toluene/ethanol solution. The measured sensitivity reaches 139 nm/RIU, in agreement with scattering matrix simulations and more than twice larger than those previously reported for Tamm plasmons. The quality factor and sensitivity yield a sensor figure of merit of 4. We also show that the electric field within the Tamm device is confined within a mode volume twice smaller than within a Fabry–Pérot resonator of comparable size according to calculations.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".