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Record W2610009897 · doi:10.1021/acs.jpclett.7b00748

Hexagonal Boron Nitride Self-Launches Hyperbolic Phonon Polaritons

2017· article· en· W2610009897 on OpenAlexafffund
Leonid Gilburd, Kris S. Kim, Kevin Ho, Daniel Trajanoski, Aniket Maiti, Duncan Halverson, Sissi de Beer, Gilbert C. Walker

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicThermal Radiation and Cooling Technologies
Canadian institutionsUniversity of Toronto
FundersStichting voor Fundamenteel Onderzoek der MaterieCanada Foundation for Innovation
KeywordsHexagonal boron nitridePhononPolaritonMaterials scienceNanoscopic scaleNanostructureCharacterization (materials science)OptoelectronicsHexagonal crystal systemPhase (matter)Boron nitrideNanotechnologyCondensed matter physicsPhysicsCrystallographyChemistryGraphene

Abstract

fetched live from OpenAlex

Hexagonal boron nitride (hBN) is a 2D material that supports traveling waves composed of material vibrations and light, and is attractive for nanoscale optical devices that function in the infrared. However, the only current method of launching these traveling waves requires the use of a metal nanostructure. Here, we show that the polaritonic waves can be launched into the 2D structure by folds within hBN, alone, taking advantage of the intrinsic material properties. Our findings suggest that structural continuity between the fold and hBN crystal is crucial for creating self-launched waves with a constant phase front. This approach offers a single material system to excite the polaritonic modes, and the approach is applicable to a broad range of 2D crystals and thus could be useful in future characterization.

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: Bench or experimental · Consensus signal: Bench or experimental
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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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 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

Citations24
Published2017
Admission routes2
Has abstractyes

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