MétaCan
Menu
Back to cohort
Record W2027153744 · doi:10.1109/map.2011.6097279

Photoresist-Based Polymer Resonator Antennas: Lithography Fabrication, Strip-Fed Excitation, and Multimode Operation

2011· article· en· W2027153744 on OpenAlexaff
Atabak Rashidian, David M. Klymyshyn, Mohammadreza Tayfeh Aligodarz, Martin Boerner, J. Mohr

Bibliographic record

VenueIEEE Antennas and Propagation Magazine · 2011
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFabricationMaterials scienceOptoelectronicsResonatorMulti-mode optical fiberLithographyBandwidth (computing)MiniaturizationDielectric resonator antennaDipole antennaAntenna (radio)OpticsElectrical engineeringComputer scienceEngineeringTelecommunicationsPhysicsNanotechnologyOptical fiber

Abstract

fetched live from OpenAlex

Artificially modified materials are becoming increasingly important in antenna design. Attractive features make polymer composites very promising materials for improving the fabrication process and antenna performance. In this study, a photosensitive polymer composite is utilized to fabricate precise dielectric-resonator antenna structures using deep-X-ray lithography. The multimode operation and miniaturization aspects of strip-fed composite antennas with very low permittivity (ε <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> <; 5 ) are investigated for the first time. The prototype antenna offers a -10 dB impedance bandwidth of 48%, from 18.8 GHz to 30.7 GHz, and gain in the range of 5 dBi. The nonradiating modes are removed by the special boundary conditions enforced by the vertical strip. Stable radiation patterns and low cross-polarization levels over the entire impedance bandwidth are therefore preserved. Further improvements in impedance bandwidth are presented, and the antenna performance and fabrication processes are discussed.

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: none
Teacher disagreement score0.944
Threshold uncertainty score0.968

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 head0.019
GPT teacher head0.215
Teacher spread0.196 · 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

Citations17
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Antennas and Propagation MagazineSame topicAntenna Design and AnalysisFrench-language works237,207