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Record W4404469645 · doi:10.1109/access.2024.3499860

Dynamic Polarization Converter Using a Polymer-Based Plasmonic Metasurface

2024· article· en· W4404469645 on OpenAlexafffund
Muhammad Saad Asad, Muhammad Alam

Bibliographic record

VenueIEEE Access · 2024
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPlasmonPolarization (electrochemistry)Materials scienceOptoelectronicsPolymerMetamaterialOpticsPhysicsChemistryComposite material

Abstract

fetched live from OpenAlex

Control of polarization is vital for many applications of photonics including sensing, communication, imaging and quantum optics. Currently available components for polarization control are often bulky and static, which limits their applications. Active metasurfaces offer a new way of achieving dynamic control of polarization with greater flexibility. We propose the design of a polymer based plasmonic metasurface to control the polarization state of the reflected light. By adjusting the temperature of the metasurface, it is possible to convert linearly polarized light to left or right handed circularly polarized light with more than 80% efficiency. It can also achieve co-polarization to cross-polarization conversion with 33% efficiency and a wide range of linear to elliptical polarization conversion. We also presented a design for THz region which provides good performance. The combination of high efficiency, large range of achievable polarization states and flexible fabrication process can make the proposed device useful for a wide range of applications. We believe this work will encourage further developments of active metasurface devices which utilize thermo-optic effect in polymers for achieving amplitude and phase tunability.

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 categoriesInsufficient payload (model declined to judge)
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 score0.145
Threshold uncertainty score1.000

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.044
GPT teacher head0.337
Teacher spread0.293 · 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.

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

Citations2
Published2024
Admission routes2
Has abstractyes

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