Characterization of Ultra‐High Temperature and Polymorphic Ceramics
Bibliographic record
Abstract
Ultra-high temperature ceramic (UHTC) and polymorphic structures often experience unique material properties for applications related to aerospace, energy and lightweight designs. Structures made from UHTCs are known to have high thermal thresholds that can withstand temperatures up to 3000 °C without changes in their crystal structure. Alternatively, polymorphic ceramics can have a change in their atomic configuration and crystalline geometry due to external stimuli well before their melting temperature. From a multiscale perspective, UHTC and its composites have a stable structure in terms of crystalline geometry and do not require atomic-level description to observe the changes in their constitutive relations due to high thermal input. However, UHTC composites can be prone to chemical reactions, such as oxidation, well before their melting temperature which leads to UHTCs exhibiting a self-healing behavior. Polymorphic structures experience a change in their crystallinity, where atomic-level characterization and constitutive relations are required in order to describe the changes in their underlying structure in real time. The presented work highlights some of the recent research in describing UHTCs, polymorphic structures and their composites through continuum and atomistic characterization of crystallinity, chemical kinetics, and multiscale depiction.
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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 | 0.001 | 0.001 |
| 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 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".