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Record W3131129396 · doi:10.1002/mop.32815

Printed <scp>concave‐like</scp> slot for bandwidth enhancement of <scp>inset‐fed</scp> patch antenna on metallic surfaces

2021· article· en· W3131129396 on OpenAlexaff
Seyi Stephen Olokede, Sameir Deif, Mojgan Daneshmand

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDirectivityPatch antennaMaterials scienceRADIUSMicrostrip antennaBandwidth (computing)WidebandMicrowaveMicrostripOpticsCladding (metalworking)Resonance (particle physics)Slot antennaAcousticsAntenna (radio)Electrical engineeringPhysicsTelecommunicationsEngineeringComposite materialComputer science

Abstract

fetched live from OpenAlex

Abstracts A rectangular patch antenna design with fundamental TM 100 mode for on‐metal applications is presented. The patch is excited by an inset‐fed microstrip feedline and optimized for better performance by varying the inset‐fed parameters. The patch is then loaded with a circular slot of radius R y at its center to create additional resonance at TM 11 mode. The radius R y is varied to elongate the circular slot into biconcave shape, to increase its electrical length. Thus, manipulating TM 11 mode with respect to TM 100 mode to achieve wideband by combining the two resonances using overlap technique. Equations of the resonance of the circular slot is stated and so is the surface area of the biconcave. The resulting antenna is etched on a 130 μm‐thick RO3003 microwave laminate and stamped on a metallic pipe cladding using the pipe as the metallic ground. The realized bandwidth is enhanced by 13% with reasonable achieved directivity. The simulated and measured results agreed reasonably with marginal discrepancy.

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 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 score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.211
Teacher spread0.201 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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