The Effect of Adjacent Materials on the Propagation of Phonon Polaritons in Hexagonal Boron Nitride
Bibliographic record
Abstract
In order to apply the ability of hexagonal boron nitride (hBN) to confine energy in the form of hyperbolic phonon polariton (HPhP) modes in photonic-electronic devices, approaches to finely control and leverage the sensitivity of these propagating waves must be investigated. Here, we show that by surrounding hBN with materials of lower/higher dielectric responses, such as air and silicon, lower/higher surface momenta of HPhPs can be achieved. Furthermore, an alternative method for preparing thin hBN crystals with minimum contamination is presented, which provides opportunities to study the sensitivity of the damping mechanism of HPhPs on adsorbed materials. Infrared scanning near-field optical microscopy (IR-SNOM) results suggest that the reflections at the upper and lower hBN interfaces are primary causes of the damping of HPhPs, and that the damping coefficients of propagating waves are highly sensitive to adjacent layers, suggesting opportunities for sensor applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".