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Record W2988042820 · doi:10.1109/access.2019.2953779

Reconfigurability Mechanisms With Scanning Rate Control for Omega-Bianisotropic Huygens’ Metasurface Leaky-Wave Antennas

2019· article· en· W2988042820 on OpenAlexaff
Elena Abdo‐Sánchez, A. J. Epstein, George V. Eleftheriades

Bibliographic record

VenueIEEE Access · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
FundersEuropean CommissionMinisterio de Ciencia, Innovación y Universidades
KeywordsReconfigurabilityRealization (probability)OpticsPhysicsElectrical impedanceBeam steeringComputer scienceWaveguideBeam (structure)AcousticsMathematicsTelecommunications

Abstract

fetched live from OpenAlex

In this paper, different reconfigurability mechanisms are proposed to scan the pointing direction at a fixed frequency of recently-proposed leaky-wave antennas based on omega-bianisotropic Huygens' metasurfaces. The tunability of both the waveguide height and the dielectric permittivity of the substrate filling the waveguide are studied, extracting theoretical expressions to predict the dependence of the beam pointing direction with the design parameters. It is shown that it is possible to control the scanning rate, a challenging task for conventional leaky-wave antennas, leading to different performances: high scanning, radiation pattern stability and backward-to-forward scanning. Additionally, the control of the scanning rate is exploited to reduce the beam squinting when varying the frequency. Simulation results of several designs with both impedance sheets and physical realization to implement the metasurfaces demonstrate the validity of the theoretical predictions and the reconfigurability potential of such a structure.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.289
Teacher spread0.241 · 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.

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

Citations18
Published2019
Admission routes1
Has abstractyes

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