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Record W1970228914 · doi:10.1109/lawp.2011.2165196

High-Gain Patch Antennas Loaded With High Characteristic Impedance Superstrates

2011· article· en· W1970228914 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials sciencePermittivityTransmission lineElectrical impedanceMicrostripPatch antennaMicrostrip antennaResonance (particle physics)Antenna gainMetamaterial antennaHigh-gain antennaOpticsAntenna (radio)AcousticsOptoelectronicsDielectricPhysicsEngineeringAntenna factorTelecommunicationsElectrical engineering

Abstract

fetched live from OpenAlex

It is shown that, under some resonance conditions, a microstrip patch antenna can be designed to achieve the highest possible gain when covered with a superstrate at the proper distance in free space. The transmission line analogy and the cavity model are used to deduce the resonance conditions required to achieve the highest gain. The resonance conditions include the condition on spacing between the antenna's substrate and the superstrate and the thickness of the superstrate. The permeability and permittivity of the superstrate are determined based on these resonant lengths and the appropriate characteristic impedance of each layer in this multilayered structure. The results are verified using both analytical and numerical methods. The effect of anisotropy of the superstrate is numerically investigated. The design criteria proposed here will reduce the total profile of the radiating system by 50% when compared to previous trends.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.191
Teacher spread0.177 · 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