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Record W2807156496 · doi:10.1038/s41598-018-20056-2

Design and Demonstration of Impedance-matched Dual-band Chiral Metasurfaces

2018· article· en· W2807156496 on OpenAlexaff
Minseok Kim, George V. Eleftheriades

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMulti-band deviceElectrical impedancePhysicsPolarization (electrochemistry)ConcentricMicrowaveComputer scienceOpticsTopology (electrical circuits)TelecommunicationsMathematicsGeometryEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

We propose a new family of impedance-matched chiral metasurfaces that offer arbitrary polarization control at two different frequencies. To this end, two main problems are addressed: (1) determination of the required surface impedances for a certain user-defined chiral functionality at two frequencies and (2) their physical realization at microwaves. The first milestone is achieved through a proposed synthesis method that combines a semi-analytical method and a nonlinear optimization technique. In particular, the impedances are computed such that the devised chiral metasurface is also impedance-matched to a terminating medium. The chiral metasurfaces are then physically realized at microwaves by cascading layers of rotated arrays of multiple concentric rectangular copper rings. We establish that these proposed unit cells offer distinct dual-resonances that can be arbitrarily and independently tuned for two orthogonal linear polarizations at each of the two operating frequencies. This allows simultaneous physical mapping of the required surface impedances at two frequencies. The versatility and generality of the proposed numerical and physical solutions are demonstrated through two design examples: A dual-band circular polarization selective surface (CPSS) and a dual-band polarization rotator (PR). The dual-band CPSS is further confirmed experimentally at 20 GHz and 30 GHz based on a free-space quasi-optical system.

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)0.004
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: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.277
Teacher spread0.246 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

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