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Record W2214066430 · doi:10.1109/tap.2015.2498941

Compact Lightweight Polymeric-Metallic Resonator Antennas Using a New Radiating Mode

2015· article· en· W2214066430 on OpenAlexafffund
Atabak Rashidian, L. Shafai

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2015
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of ManitobaPeraso Technologies (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsSTRIPSResonatorMaterials scienceMiniaturizationDielectric resonator antennaBandwidth (computing)PermittivityExcited stateOptoelectronicsAcousticsDielectricComputer sciencePhysicsComposite materialTelecommunications

Abstract

fetched live from OpenAlex

A new approach is introduced to show that bulk polymers with metallic plates/strips can be employed to design compact lightweight resonator antennas. A new fundamental mode is excited inside the polymer, based on the special boundary conditions enforced by the metallic plates and strip. By properly adjusting the physical parameters (e.g., the gap between metallic plate and strip), the mode is excited in an appropriate shape and significant miniaturization along with good radiation performance is achieved. An antenna structure is fabricated using acrylic (ε <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> = 3) and the measured results are compared with the results of other compact antennas, which can be realized using very high-permittivity materials. Besides over 70% reduction in weight, outstanding antenna features such as 10% impedance bandwidth, 5.7 dBi gain, over 90% efficiency, and dimensions smaller than λ/6, make the proposed approach more suitable for designing compact lightweight antennas.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.251
Teacher spread0.218 · 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 designSimulation or modeling
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
Published2015
Admission routes2
Has abstractyes

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