Near-Zero Thermal Expansion in Freeze-Cast Composite Materials
Bibliographic record
Abstract
Most materials expand when heated, which can lead to thermal stress and even failure. Whereas thermomiotic materials exhibit negative thermal expansion, the creation of materials with near-zero thermal expansion presents an ongoing challenge due to the need to optimize thermal and mechanical properties simultaneously. The present work describes the preparation and properties of polymer–ceramic composites with low thermal expansion. Ceramic scaffolds, prepared by freeze-casting of low-thermal-expansion Al2W3O12, were impregnated with poly(methylmethacrylate) (PMMA). The resulting composites can have a coefficient of thermal expansion as low as 2 × 10−6 K−1, and hardness values of 4.0 ± 0.3 HV/5 (39 ± 3 MPa) and 16 ± 3 HV/5 (160 ± 30 MPa) parallel and perpendicular to the ice growth, respectively. The higher hardness perpendicular to the ice growth direction indicates that the PMMA is acting to improve the mechanical properties of the composite.
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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 | 0.000 | 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 | 0.001 |
| 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".