Predicting Phonon Thermal Transport in Two-Dimensional Graphene-Boron Nitride Superlattices at the Short-Period Limit
Bibliographic record
Abstract
Two-dimensional superlattices are promising alternatives to traditional semiconductors for manufacturing power-dissipating devices with enhanced thermal and electronic properties. The goal of this work is to investigate the influence of the superlattice secondary periodicity and atomic interface orientation on the phonon properties and thermal conductivity of two-dimensional superlattices of graphene and boron nitride. We have employed harmonic lattice dynamics to predict the phonon group velocities and specific heats, and molecular dynamics to extract the relaxation times from normal mode analysis in the frequency domain. Density functional perturbation theory is applied to validate the phonon dispersion curves. The Boltzmann transport equation under single relaxation time approximation is then used to predict the thermal conductivities of the superlattices in the zigzag and armchair orientations with periodicities between one and five. Our results showed that the thermal conductivities increased by 15.68% when reducing the superlattice period from two to one. In addition, thermal conductivities parallel to the interface increase by 20.15% when switching the orientation from armchair to zigzag.
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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) | 0.000 | 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".