Extreme in-plane thermal conductivity anisotropy in Rhenium-based dichalcogenides
Bibliographic record
Abstract
Abstract Anisotropies in thermal conductivity are important for thermal management in a variety of applications, but also provide insight on the physics of nanoscale heat transfer. As materials are discovered with more extreme transport properties, it is interesting to ask what the limits are for how dissimilar the thermal conductivity can be along different directions in a crystal. Here we report on the thermal properties of rhenium-based transition metal dichalcogenides (TMDs), specifically rhenium disulfide (ReS2) and rhenium diselenide (ReSe2), highlighting their extraordinary thermal conductivity anisotropy. Along the basal crystal plane of ReS2, a maximum of 169 ± 11 W mK−1 is detected along the b-axis and a minimum of 53 ± 4 W mK−1 perpendicular to it. For ReSe2, the maximum and minimum values of 116 ± 3 W mK−1 and 27 ± 1 W mK−1 are found to lie 60° and 150° away from the b-axis, along the polarization direction of some of the principal Raman modes. These measurements demonstrate a remarkable anisotropy of 3.2 × and 4.3 × in the conductivity within the crystal basal planes, respectively. The through-plane thermal conductivities, recorded at 0.66 ± 0.01 W mK−1 for ReS2 and 2.31 ± 0.01 W mK−1 for ReSe2, highlight the impact of their layered structures, contributing to notably high in-plane to through-plane thermal conductivity ratios of 256 × for ReS2 and 50 × for ReSe2. This research demonstrates the unique thermal properties that these comparatively underexplored TMDs have, shedding light on the need for further exploration into the intricate thermal behavior of such materials, while underscoring their potential significance for future applications in the fields of semiconductor devices and nanotechnology.
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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".