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Record W2140141565 · doi:10.1109/mwsym.2012.6259465

Non-reciprocal gyrotropy in graphene: New phenomena and applications

2012· article· en· W2140141565 on OpenAlexaff
Dimitrios L. Sounas, Thomas Szkopek, Christophe Caloz

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsMcGill UniversityPolytechnique Montréal
Fundersnot available
KeywordsGrapheneFaraday effectFaraday cageMagneto-optic effectMagnetic fieldMicrowaveTerahertz radiationCyclotron resonanceMaterials sciencePhysicsOpticsElectrical conductorElectric fieldReciprocalPlasmonOptoelectronicsCondensed matter physicsFaraday rotatorCyclotronNanotechnology

Abstract

fetched live from OpenAlex

The non-reciprocal gyrotropic properties of magnetically biased graphene are presented and subsequent potential applications are proposed. Graphene exhibits strong Faraday rotation at microwave frequencies. The amount of rotation can be controlled by both an applied static magnetic field, which controls the cyclotron resonance frequency, and an applied static electric field, which tunes the chemical potential of the material. As an application of Faraday rotation, we present, beyond recently reported non-reciprocal components, a waveguide setup for the extraction of the conductivity tensor of graphene. Moreover, it is shown that a graphene strip supports surface magneto-plasmon modes, each of which propagates along one of its edges, at THz frequencies. Exploiting this effect, a non-reciprocal phase shifter can be realized by placing a conducting plate along one side of the strip.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.001
Scholarly communication0.0010.001
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 head0.020
GPT teacher head0.290
Teacher spread0.271 · 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 designTheoretical or conceptual
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

Citations4
Published2012
Admission routes1
Has abstractyes

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