Low-temperature phonon thermal conductivity of single-crystalline<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Nd</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mi mathvariant="normal">Cu</mml:mi><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:mrow></mml:math>: Effects of sample size and surface roughness
Bibliographic record
Abstract
The effect of sample size and surface roughness on the phonon thermal conductivity ${\ensuremath{\kappa}}_{p}$ of ${\mathrm{Nd}}_{2}\mathrm{Cu}{\mathrm{O}}_{4}$ single crystals was studied down to $50\phantom{\rule{0.3em}{0ex}}\mathrm{mK}$. At $0.5\phantom{\rule{0.3em}{0ex}}\mathrm{K}$, ${\ensuremath{\kappa}}_{p}$ is proportional to $\sqrt{A}$, where $A$ is the cross-sectional area of the sample. This demonstrates that ${\ensuremath{\kappa}}_{p}$ is dominated by boundary scattering below $0.5\phantom{\rule{0.3em}{0ex}}\mathrm{K}$ or so. However, the expected ${T}^{3}$ dependence of ${\ensuremath{\kappa}}_{p}$ is not observed down to $50\phantom{\rule{0.3em}{0ex}}\mathrm{mK}$. Upon roughing the surfaces, the ${T}^{3}$ dependence is restored, showing that departures from ${T}^{3}$ are due to specular reflection of phonons off the mirrorlike sample surfaces. We propose an empirical power law fit to ${\ensuremath{\kappa}}_{p}\ensuremath{\sim}{T}^{\ensuremath{\alpha}}$ (where $\ensuremath{\alpha}<3$) in cuprate single crystals. Using this method, we show that recent thermal conductivity studies of Zn doping in $\mathrm{Y}{\mathrm{Ba}}_{2}{\mathrm{Cu}}_{3}{\mathrm{O}}_{y}$ reaffirm the universal heat conductivity of $d$-wave quasiparticles at $T\ensuremath{\rightarrow}0$.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.222 | 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; both teacher heads agree on what is shown here.
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".