MétaCan
Menu
Back to cohort
Record W2125289293 · doi:10.1109/tasc.2005.850167

Analysis and Design of Superconducting Left-Handed Transmission Lines

2005· article· en· W2125289293 on OpenAlexaff
H. Salehi, A. Hamed Majedi, Raafat R. Mansour

Bibliographic record

VenueIEEE Transactions on Applied Superconductivity · 2005
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsKinetic inductanceInductanceTransmission lineCoplanar waveguideGround planeMaterials scienceMicrostripResonatorElectric power transmissionPropagation constantOptoelectronicsEquivalent series inductanceOpticsPhysicsElectrical engineeringTelecommunicationsMicrowaveComputer scienceVoltage

Abstract

fetched live from OpenAlex

In this paper, for the first time, we study the properties of a superconductive-based left-handed transmission line (SLHTL). The effect of the kinetic inductance on the propagation constant of the left-handed transmission line is analyzed. It is shown that increasing the kinetic inductance decreases both the bragg frequency and the negative index frequency band of a distributed LHTL. A Coplanar waveguide structure is proposed to realize the LHTL. It is shown that the CPW structure has the capability of increasing the kinetic inductance of the TL by narrowing the spacing between the line and the ground plane because they are deposited on the same side of the substrate. This was not possible in a microstrip line as the spacing between the line and the ground is equal to the substrate thickness and is usually fixed. Furthermore, the dependency of the kinetic inductance to the bias current has been employed to design a tunable SLHTL. Possible applications of the tunable SLHTL in the design of miniaturized tunable resonators and filters 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 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)0.0010.000

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 head0.042
GPT teacher head0.269
Teacher spread0.228 · 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

Citations30
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Applied SuperconductivitySame topicMetamaterials and Metasurfaces ApplicationsFrench-language works237,207