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Record W2791110766

Enhancement of microstrip antennas performance using electromagnetic bandgap substrates

2005· article· en· W2791110766 on OpenAlexaboutno aff
Dan Qu

Bibliographic record

VenueMspace (University of Manitoba) · 2005
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMicrostrip antennaMicrostripOptoelectronicsMaterials scienceBand gapElectronic engineeringOpticsComputer sciencePhysicsAntenna (radio)TelecommunicationsEngineering
DOInot available

Abstract

fetched live from OpenAlex

structures as a substrate for applications in microstrip patch antennas.First, the basic background theory of microstrip patch antennas and electromagnetic bandgap structures is reviewed.The equations for design of patch antennas and the basics of EBG structures are introduced.Then, microstrip patch antennas using high impedance EBG substrates, within the bandgaps are investigated.The bandgaps of the EBG structure are found, and patch antennas are designed to work within these bandgaps, to study their properties.Both single layer and two layer EBG structures are used in this study, and their effects on the resonant frequency, minimum Srr, bandwidth, radiation patterns and gain of the antennas are investigated.Then, investigations are conducted for microstrip patch antennas outside the bandgaps, both lower and higher frequency bands.Again, the effects of the EBGs on the resonant frequency, minimum S, bandwidth, radiation patterns and gain of the antennas are investigated.The structures are simulated using the commercial software Ansoft Ensemble which is based on the method of moments (MoM).In order to conf,rrm the simulation results, several antennas are fabricated in the Antenna Laboratory and the Machine Shop at the University of Manitoba.The measured results agree well with the simulation data.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.536

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 head0.011
GPT teacher head0.175
Teacher spread0.163 · 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

Citations5
Published2005
Admission routes1
Has abstractyes

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