Predictions of thermal expansion coefficients of rare-earth zirconate pyrochlores: A quasi-harmonic approximation based on stable phonon modes
Bibliographic record
Abstract
Rare-earth (RE) pyrochlores are considered as promising candidate materials for the thermal barrier coating. In this study, we performed first-principles calculations, augmented by quasi-harmonic phonon calculations, to investigate the thermal expansion behaviors of several RE2Zr2O7 (RE = La, Nd, Sm, Gd) pyrochlores. Our findings show that RE2Zr2O7 pyrochlores exhibit low-lying optical phonon frequencies that correspond to RE-cation rattling vibrational modes. These frequencies become imaginary upon volume expansion, preventing correct determination of the free energy versus volume relation and thereby quantification of thermal expansion using QH phonon calculations. To address this challenge, we proposed a QH approximation approach based on stable phonon modes where the RE-cation rattling modes were systematically eliminated. This approach is shown to provide accurate predictions of the coefficients of thermal expansion (CTEs) of RE2Zr2O7 pyrochlores, in good agreement with experimental measurements and data from first-principles molecular dynamics simulations. In addition, we showed that the QH Debye model considerably overestimates the magnitudes and wrongly predicts the trend for the CTEs of RE2Zr2O7 pyrochlores.
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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 | 0.000 |
| 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".