Bibliographic record
Abstract
We calculate the heat flux and electron-phonon thermal conductance in a disordered graphene sheet, going beyond a Fermi's golden rule approach to fully account for the modification of the electron-phonon interaction by disorder. Using the Keldysh technique combined with standard impurity averaging methods in the regime ${k}_{F}l\ensuremath{\gg}1$ (where ${k}_{F}$ is the Fermi wave vector and $l$ is the mean free path), we consider both scalar potential (i.e., deformation potential) and vector-potential couplings between electrons and phonons. We also consider the effects of electronic screening at the Thomas-Fermi level. We find that the temperature dependence of the heat flux and thermal conductance is sensitive to the presence of disorder and screening, and reflects the underlying chiral nature of electrons in graphene and the corresponding modification of their diffusive behavior. In the case of weak screening, disorder enhances the low-temperature heat flux over the clean system (changing the associated power law from ${T}^{4}$ to ${T}^{3}$), and the deformation potential dominates. For strong screening, both the deformation potential and vector-potential couplings make comparable contributions, and the low-temperature heat flux obeys a ${T}^{5}$ power law.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 0.001 |
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".