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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

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 score0.003
Threshold uncertainty score0.350

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 science0.0010.000
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 head0.006
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