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Record W3135887102 · doi:10.1109/tap.2021.3060084

Analysis and Design of General Printed Circuit Board Metagratings With an Equivalent Circuit Model Approach

2021· article· en· W3135887102 on OpenAlexaff
Gengyu Xu, George V. Eleftheriades, Sean V. Hum

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEquivalent circuitPrinted circuit boardGratingScattering parametersFloquet theoryElectrical impedanceHarmonicsElectrical elementComputer scienceScatteringElectronic engineeringTopology (electrical circuits)OpticsPhysicsElectrical engineeringEngineeringVoltageNonlinear system

Abstract

fetched live from OpenAlex

An accurate equivalent circuit model (ECM) for general multiwire multiorder printed circuit board (PCB) metagratings (MGs) is developed. The effective impedances of the grating wires are modeled as lumped loads in the ECM. The numerous propagating Floquet harmonics supported by the grating are modeled as circuit ports. Based on the desired field transformation for the MG, a set of required scattering parameters for its ECM is derived. The equivalent lumped loads are subsequently optimized to realize these parameters, which is analogous to shaping the diffraction pattern of the MG to match the desired functionality. Within this framework, it is possible to encode multiple functions into a single device by simultaneously optimizing all relevant entries of the ECM scattering matrix. Using the proposed technique, an angle-multiplexed multifunctional MG is designed and investigated.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.039
GPT teacher head0.238
Teacher spread0.199 · 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

Citations46
Published2021
Admission routes1
Has abstractyes

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