Strong low-energy rattling modes enabled liquid-like ultralow thermal conductivity in a well-ordered solid
Bibliographic record
Abstract
ABSTRACT Crystalline solids exhibiting inherently low lattice thermal conductivity (κL) are of great importance in applications such as thermoelectrics and thermal barrier coatings. However, κL cannot be arbitrarily low and is limited by the minimum thermal conductivity related to phonon dispersions. In this work, we report the liquid-like thermal transport in a well-ordered crystalline CsAg5Te3, which exhibits an extremely low κL value of ∼0.18 Wm−1K−1. On the basis of first-principles calculations and inelastic neutron scattering measurements, we find that there are lots of low-lying optical phonon modes at ∼3.1 meV hosting the avoided-crossing behavior with acoustic phonons. These strongly localized modes are accompanied by weakly bound rattling Ag atoms with thermally induced large amplitudes of vibrations. Using the two-channel model, we demonstrate that coupling of the particle-like phonon modes and the heat-carrying wave-like phonons is essential for understanding the low κL, which is heavily deviated from the 1/T temperature dependence of the standard Peierls theory. In addition, our analysis indicates that the soft structural framework with liquid-like motions of the fluctuating Ag atoms is the underlying cause that leads to the suppression of the heat conduction in CsAg5Te3. These factors synergistically account for the ultralow κL value. Our results demonstrate that the liquid-like heat transfer could indeed exist in a well-ordered crystal.
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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".