Atomistic and experimental study on thermal conductivity of bulk and porous cerium dioxide
Bibliographic record
Abstract
Abstract Cerium dioxide (CeO 2 ) is a surrogate material for traditional nuclear fuels and an essential material for a wide variety of industrial applications both in its bulk and nanometer length scale. Despite this fact, the underlying physics of thermal conductivity ( k L ), a crucial design parameter in industrial applications, has not received enough attention. In this article, a systematic investigation of the phonon transport properties was performed using ab initio calculations unified with the Boltzmann transport equation. An extensive examination of the phonon mode contribution, available three-phonon scattering phase space, mode Grüneisen parameter and mean free path (MFP) distributions were also conducted. To further augment theoretical predictions of the k L , measurements were made on specimens prepared by spark plasma sintering using the laser flash technique. Since the sample porosity plays a vital role in the value of measured k L , the effect of porosity on k L by molecular dynamics (MD) simulations were investigated. Finally, we also determined the nanostructuring effect on the thermal properties of CeO 2 . Since CeO 2 films find application in various industries, the dependence of thickness on the in-plane and cross-plane k L for an infinite CeO 2 thin film was also reported.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".