MétaCan
Menu
Back to cohort
Record W7132956151

Resonance-cone propagation in continuous transmission-line grids and microwave applications

2007· dissertation· W7132956151 on OpenAlexfundno aff
Omar Siddiqui

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsDiplexerMicrowaveDispersion (optics)HarmonicMultiplexerMetamaterialGridSplitter
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents a novel approach to synthesizing a hyperbolically dispersive metamaterial by forming a continuous (unloaded) periodic transmission-line grid with rectangular unit-cells over a ground plane. The dispersion properties of the hyperbolic grids are examined by performing periodic analysis. The hyperbolic dispersive effects occur in second and higher order harmonic bands because the periodicity of the grids is on the order of half-wavelength. Frequency-dependent phenomena associated with the hyperbolic dispersion such as resonance-cone formation and their negative refraction and focusing, are demonstrated by plane-wave and circuit simulations, and are experimentally verified in microstrip-based grids. It is shown that by exploiting the unique dispersion characteristics of the grids, spatial-filtering electromagnetic devices such as passive spectrum analyzers, multiplexers and demultiplexers can be designed. Representative microwave devices including a 3 GHz/6 GHz harmonic splitter and a 5.8/6.2 GHz diplexer are designed and practically implemented. Since these grids are synthesized by simply printing transmission lines, they are easy to fabricate at a low cost and are potentially scalable to millimeter and Tera-hertz frequencies.

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 head0.023
GPT teacher head0.341
Teacher spread0.318 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicMetamaterials and Metasurfaces ApplicationsFrench-language works237,207