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Record W4392719381 · doi:10.1109/ojap.2024.3375153

Design of Wideband Reflectarray and Transmitarray Antennas With Low Sidelobe and Cross-Polarization Levels Using a Multifunctional Ultrathin Metasurface

2024· article· en· W4392719381 on OpenAlexaff
Yufang Wang, Yuehe Ge, Zhizhang Chen, Ziheng Zhou

Bibliographic record

VenueIEEE Open Journal of Antennas and Propagation · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsDalhousie University
FundersNatural Science Foundation of Fujian ProvinceNational Natural Science Foundation of China
KeywordsWidebandPolarization (electrochemistry)OpticsOptoelectronicsMaterials sciencePhysicsAcoustics

Abstract

fetched live from OpenAlex

Ensuring a low cross-polarization level (CPL) is imperative in the design of antennas with a low sidelobe level (SLL). This paper introduces an innovative approach for designing wideband, high-gain, low-sidelobe, and low-cross-polarization reflectarray (RA) and transmitarray (TA) antennas. The methodology leverages a groundbreaking metasurface endowed with the capability for independent amplitude and phase manipulation in both transmission and reflection modes. Initial characterization robustly verifies the metasurface’s proficiency in independently controlling amplitude and phase in reflection and transmission modes. Importantly, the study demonstrates that this metasurface enables the straightforward attainment of low CPL in the design of low-SLL RA and TA antennas. The study progresses to the design, fabrication, and testing of three RA and TA antennas. The obtained simulated and measured results affirm their exceptional performance in terms of wideband, high-gain, low-SLL, and low-CPL characteristics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.292
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2024
Admission routes1
Has abstractyes

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