A Wideband High Gain Transmit‐Array Antenna Exploiting Polarization‐Rotated Metasurface Cell
Bibliographic record
Abstract
ABSTRACT A novel polarization‐insensitive transmit‐array (TA) antenna using linear polarization‐rotated (PR) metasurface (MS) unit cells has been proposed in this article. Firstly, we design a wideband polarization‐insensitive polarization‐rotated MS unit cell. The MS cell can provide high transmission for incident linear polarized waves with polarization rotation by 90°. Then, we investigate the stability of the MS cell under the oblique incident wave. The proposed MS cell keeps a stable response under oblique incident wave over ± 30°. To verify the excellent performance of the proposed MS. We design a high‐gain TA antenna consisting of a standard feed horn and an aperture with a gradient phase. The gradient phase compensation is provided by varying the geometric dimension of the proposed MS. The obtained TA antenna works in a wide band with high gain. We fabricated the aperture and set up a prototype of TA antenna to verify our work. We measure the TA antenna and the results show a wide operating band from 14.2 to 18 GHz with a pick gain of 23.9 dBi. The favorable performance of the TA antenna is a good candidate in satellite systems and long‐distance satellite system. Furthermore, the angular stability of the MS cell is also verified by realizing the beam scanning performance. An over ± 30° scan range is obtained. Good beam scanning can be used in radar detection and expand signal coverage.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Antenna engineering paper on a metasurface-based transmit-array; the object is a device design.
This engineering study develops and tests a metasurface antenna, not research practice.
Antenna engineering design of a transmit-array metasurface; applied physics/engineering.
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) | 0.001 | 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".