A Honeycomb Mesh-Type Reflectarray with High Optical Transparency for Millimeter-Wave Applications
Bibliographic record
Abstract
An optically-transparent reflectarray (RA) operating at 28 GHz, based on a honeycomb metal-meshing scheme and fine metal line (FML) structures, is proposed. The RA unit cells consist of hexagonal rings with linewidths of$50 \mu \mathrm{m}$and a 1 mm -thick fused silica$\left(\varepsilon_{\mathrm{r}}=4.0\right)$substrate backed by a metal ground plane with perforations in a honeycomb pattern. Additional punctures in the mesh are created in between each honeycomb perforation to further enhance the transparency. The unit cell uses two different hexagonal ring elements to achieve a wide phase range of 298°. Across the various unit cell ring geometries, a peak return loss of 0.77 dB is realized. Simulations of 1D and 2D RA structures are demonstrated using Ansys HFSS. The 2D RA achieves a peak gain of 19.2 dB with a sidelobe level (SLL) of -19 dB. The overall RA structure achieves a transparency of 85.1% and may be integrated with infrastructure such as glass panels to improve signal coverage.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".