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Record W2327314303 · doi:10.1021/nn504093g

Mid-infrared Polaritonic Coupling between Boron Nitride Nanotubes and Graphene

2014· article· en· W2327314303 on OpenAlexafffund
Xiaoji G. Xu, Jian‐Hua Jiang, Leonid Gilburd, Rachel G. Rensing, Kenneth S. Burch, Chunyi Zhi, Yoshio Bando, Dmitri Golberg, Gilbert C. Walker

Bibliographic record

VenueACS Nano · 2014
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Education, Culture, Sports, Science and Technology
KeywordsGrapheneMaterials scienceBoron nitridePolaritonGraphene nanoribbonsInfraredSurface phononOptoelectronicsSurface plasmon polaritonPlasmonPhononNanophotonicsNanotechnologySurface plasmonCondensed matter physicsOpticsPhysics

Abstract

fetched live from OpenAlex

Boron nitride (BN) is considered to be a promising substrate for graphene-based devices in part because its large band gap can serve to insulate graphene in layered heterostructures. At mid-infrared frequencies, graphene supports surface plasmon polaritons (SPPs), whereas hexagonal-BN (h-BN) is found to support surface phonon polaritons (SPhPs). We report on the observation of infrared polaritonic coupling between graphene SPPs and boron nitride nanotube (BNNT) SPhPs. Infrared scattering type scanning near-field optical microscopy is used to obtain spatial distribution of the two types of polaritons at the nanoscale. The observation suggests that those polaritons interact at the nanoscale in a one-dimensional/two-dimensional (1D/2D) geometry, exchanging energy in a nonplanar configuration at the nanoscale. Control of the polaritonic interaction is achieved by adjustment of the graphene Fermi level through voltage gating. Our observation suggests that boron nitride nanotubes and graphene can interact at mid-infrared frequencies and coherently exchange their energies at the nanoscale through the overlap of mutual electric near field of surface phonon polaritons and surface plasmon polaritons. Such interaction enables the design of nano-optical devices based on BNNT-graphene polaritonics in the mid-infrared range.

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: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.740

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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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

Citations42
Published2014
Admission routes2
Has abstractyes

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