Generalized Synthesis Technique for High-Order Low-Profile Dual-Band Frequency Selective Surfaces
Bibliographic record
Abstract
A systematic design method for high-order dualband bandpass frequency selective surfaces (FSSs) with a low profile is derived from classical filter theory and presented here. To complement the design procedure, a multilayer double-slot resonator unit cell topology is proposed for realizing dual-band operations. For simplicity, the resonators are made to work for only a single polarization. To design the FSS, first, a classical dual-band bandpass filter circuit is designed by performing successive frequency transformations on a lowpass prototype. The filter is then transformed into a form resembling the equivalent circuit of the proposed multilayer FSS structure. Finally, the transformed filter is mapped to a set of FSS geometrical parameters. The method presents very few inherent limitations to realizing a diverse range of filter responses. The resulting designs lend themselves to fabrication since very few layers of metallization are required. Two FSSs with third-order passbands at 4 and 7 GHz but different passband characteristics are designed and verified numerically. One of the designs is fabricated and experimentally verified. The overall thickness of the designs is 0.08λlwhere λlis the free-space wavelength at 4 GHz. The unit cell size is approximately λl/8.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".