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Record W2105457219 · doi:10.1109/lmwc.2003.808719

Transmission line models for negative refractive index media and associated implementations without excess resonators

2003· article· en· W2105457219 on OpenAlexaff
George V. Eleftheriades, Omar Siddiqui, Ashwin K. Iyer

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2003
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsResonatorTransmission lineMetamaterialSplit-ring resonatorRefractive indexWidebandCapacitorMicrowaveElectric power transmissionPlanarMaterials scienceEquivalent circuitMicrostripOpticsOptoelectronicsPhysicsElectrical engineeringTelecommunicationsComputer scienceVoltageEngineering

Abstract

fetched live from OpenAlex

Recently, three-dimensional composite periodic media comprising split-ring resonators (SRR) and thin wires have been shown to exhibit a negative refractive index in the frequency range around the SRR resonance. In this letter, we propose transmission line models for studying and interpreting the electromagnetic propagation behavior of such materials. Based on these equivalent transmission line models, we show that by periodically loading a network of transmission lines with series capacitors and shunt inductors, a negative refractive index medium can be synthesized without excess resonators, thus leading to wideband behavior. These proposed media have tailorable properties over a broad frequency range. Moreover, they are completely planar, frequency scalable, more compact, and easier to implement for RF/microwave circuit applications than their SRR/wire counterparts.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.042
GPT teacher head0.284
Teacher spread0.242 · 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 designSimulation or modeling
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

Citations249
Published2003
Admission routes1
Has abstractyes

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