New approach for extraordinary transmission through an array of subwavelength apertures using thin ENNZ metamaterial liners
Bibliographic record
Abstract
Extraordinary transmission (ET) through a periodic array of subwavelength apertures on a perfect metallic screen has been studied extensively in recent years, and has largely been attributed to diffraction effects, for which the periodicity of the apertures, rather than their dimensions, dominates the response. The transmission properties of the apertures at resonance, on the other hand, are not typically considered 'extraordinary' because they may be explained using more conventional aperture-theoretical mechanisms. This work describes a novel approach for achieving ET in which subwavelength apertures are made to resonate by lining them using thin, epsilon-negative and near-zero (ENNZ) metamaterials. The use of ENNZ metamaterials has recently proven successful in miniaturizing circular waveguides by strongly reducing their natural cutoff frequencies, and the theory is adapted here for the design of subwavelength apertures in a metallic screen. We present simulations and proof-of-concept measurements at microwave frequencies that demonstrate ET for apertures measuring one-quarter of a wavelength in diameter and suggest the potential for even more dramatic miniaturization simply by engineering the ENNZ metamaterial dispersion. The results exhibit a fano-like profile whose frequency varies with the properties of the metamaterial liner, but is independent of period. It is suggested that similar behaviour can be obtained at optical frequencies, where ENNZ metamaterials may be realized using appropriately arranged chains of plasmonic nanoparticles.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".