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Record W2132751476

Air-gap Standing Parallel Strips waveguide for X-ray lithography fabrication: Characteristics and antenna application

2011· article· en· W2132751476 on OpenAlexaff
Mohammadreza Tayfeh Aligodarz, David M. Klymyshyn, Atabak Rashidian

Bibliographic record

VenueEuropean Conference on Antennas and Propagation · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSTRIPSFabricationReflection coefficientMaterials scienceOpticsDipole antennaMicrowaveLithographyBandwidth (computing)Electronic circuitExtremely high frequencyImpedance matchingWaveguideAntenna (radio)Slot antennaOptoelectronicsElectrical impedanceElectrical engineeringTelecommunicationsPhysicsComputer scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

X-ray lithography fabrication has the ability to produce high-aspect ratio structures with smooth side walls and precise lateral details. Air-gap Standing Parallel Strips waveguide and related microwave circuits and antennas are a new approach to employ these features, providing low loss microwave circuits that are highly attractive for high frequency and millimeter-wave applications. In this work, various characteristics of this waveguide are studied and design graphs are provided for different structural parameters. A half-wavelength dipole antenna is designed and analyzed as an example to demonstrate the capabilities of standing parallel strips structures in high frequency applications. A −10 dB impedance bandwidth of 23% is achieved for the designed antenna; near perfect matching (reflection coefficient is −50 dB at the resonant frequency of 20 GHz) is realized using a slight taper in the feed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.043
GPT teacher head0.223
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2011
Admission routes1
Has abstractyes

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