Highly tunable thermal conductivity of C3N under tensile strain: A first-principles study
Bibliographic record
Abstract
In this study, the phonon thermal transport in monolayer C3N under biaxial strains ranging from 0% to 10% has been investigated using first-principles calculations based on the Boltzmann transport equation. It is found that the thermal conductivity κ of C3N shows a nonmonotonic up-and-down behavior in response to tensile strain, and the maximum κ occurs at a strain of 6%. Interestingly, the thermal conductivity of monolayer C3N shows a remarkable high strain tunability, as its value at 6% strain is about 13.2 times higher than the value of κ in an unstrained monolayer. A mode-by-mode phonon level analysis shows that a competition between different phonon properties is responsible for such variations in the thermal conductivity. We found that the decrease in group velocity of the transverse acoustic, longitudinal acoustic, and optical modes as well as the increase in the three-phonon phase space of all the acoustic modes tend to reduce the thermal conductivity with strain. However, the group velocity of the z-direction acoustic mode and the Grüneisen parameter of all acoustic modes change in the direction of increasing the phonon lifetime and the thermal conductivity with increasing strain. Upon stretching, the change in the Grüneisen parameter and the phonon lifetime of the acoustic modes is found to be drastically higher than the change in other properties. The competition between these opposite effects leads to the up-and-down behavior of the thermal conductivity in C3N.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".