Martensitic Transformation Temperatures of Ceramics
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Bibliographic record
Abstract
The renewed interest in shape memory and toughened ceramics for small‐scale applications makes the relationship between the chemistry of the ceramics and martensitic transformation temperatures (forward and reverse temperatures M s and A s ) of paramount importance. Dependence of transformation temperatures of the ceramics with shape memory effect and/or martensitic phase change on valence electron ratio (VER), number of valence electrons ( e v ), and average atomic number of the ceramics ( Z ) is investigated. Depending on chemical composition, the ceramics have average numbers of valence electrons (4.571 ≤ e v ≤ 5.667), Z = 13–29.333, and VER in the range of (0.17–0.44). A clear correlation of transformation temperatures to VER for most ceramics is found. M s and A s both decrease with increasing VER. Aliovalent doping alters e v and makes it influential in controlling the transformation temperatures. The influence of VER, e v , Z , and the suppressive effect of oversized solutes on M s is addressed.
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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 | 0.000 | 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) | 0.002 | 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 it