Impact of dimensional crossover on phonon transport in van der Waals materials: A case study of graphite and graphene
Bibliographic record
Abstract
Using first-principles modeling we investigate how phonon transport evolves in layered/van der Waals materials when going from 3D to 2D, or vice versa, by gradually pulling apart the atomic layers in graphite to form graphene. Focus is placed on identifying the features impacting thermal conductivity that are likely shared with other layered materials. The thermal conductivity $\ensuremath{\kappa}$ of graphite is found to be lower than that of graphene in large part due to changes in the phonon dispersion driven by van der Waals coupling. Specifically, as the atomic layers are brought closer together, the acoustic flexural phonons in graphene form low-energy optical flexural phonons in graphite that possess lower in-plane velocities, density of states, and phonon occupation, thus reducing $\ensuremath{\kappa}$. Similar dispersion changes, and impact on thermal conductivity, can be expected in other van der Waals materials when transitioning from 2D to 3D. Our findings also indicate that the selection rules in graphene, which reduce phonon-phonon scattering and contribute to its large $\ensuremath{\kappa}$, effectively hold as the atomic layers are brought together to form graphite. While the selection rules do not strictly apply to graphite, in practice reduced scattering is observed due in part to the weak interlayer coupling. This suggests that some bulk van der Waals materials may have lower phonon-phonon scattering rates than other nonlayered bulk materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".