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Record W4290710833 · doi:10.1109/tap.2022.3195500

Feasible Extraction Method for Electromagnetic Properties of Multilayer Metamaterials With Short-Circuit Termination

2022· article· en· W4290710833 on OpenAlexaff
Uğur Cem Hasar, Gökhan Öztürk, Yunus Kaya, Musa Bute, Muharrem Karaaslan, Joaquim J. Barroso, Omar M. Ramahi, Mehmet Ertuğrul

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Waterloo
FundersTürkiye Bilimsel ve Teknolojik Araştırma Kurumu
KeywordsMetamaterialMaterials scienceScatteringEquivalent circuitScattering parametersLayer (electronics)Reflection (computer programming)Extraction (chemistry)OptoelectronicsTopology (electrical circuits)OpticsComputer sciencePhysicsComposite materialMathematics

Abstract

fetched live from OpenAlex

An extraction technique is proposed for electromagnetic characterization of metal-backed multilayer metamaterial (MM) structures demonstrating reflection-asymmetric property. It uses recursive scattering parameters for direct and reversed configurations of a multilayer structure. The algorithm was validated by comparing the extracted electromagnetic properties of multilayer structures composed of different MM unit cells with those determined by one-layer-only S-parameter methods. Two-layer and three-layer multilayer structures composed of MM slabs with C-shaped and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> -shaped rings and an FR4 material were fabricated and measured for experimental validation. A sensitivity analysis was also conducted to quantitatively evaluate the performance of our method against a small air gap between the multilayer structures and the short-circuit termination and between adjacent MM slabs within these structures. Strong agreement was observed between the resulted obtained using our method and measurements.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.663
Threshold uncertainty score0.452

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 head0.032
GPT teacher head0.262
Teacher spread0.230 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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