Novel fabrication route for porous silicon carbide ceramics through the combination of <i>in situ</i> polymerization and reaction bonding techniques
Bibliographic record
Abstract
ABSTRACT For the first time, an in situ polymerization technique was applied to produce mullite‐bonded porous SiC ceramics via a reaction bonding technique. In this study, SiC microsized particles and alumina nanopowders were successfully coated by polyethylene (PE), which was synthesized from the particle surface in a slurry phase reactor with a Ziegler–Natta catalyst system. The thermal studies of the resulting samples were performed with differential scanning calorimetry and thermogravimetric analysis. The morphology analysis obtained by transmission electron microscopy and scanning electron microscopy (SEM) confirmed that PE was successfully grafted onto the particle surface. Furthermore, the obtained porous ceramics were characterized in terms of their morphologies, phase composition, open porosity, pore size distribution, and mechanical strength. SEM observations and mercury porosimtery analysis revealed that the quality of the dispersion of nanosized alumina powder into the microsized SiC particles was strongly enhanced when the particles were coated by polymers with in situ polymerization. This resulted in a higher strength and porosity of the formed ceramic porous materials with respect to the traditional process. In addition, the X‐ray diffraction results reveal that the amount of mullite as the binder increased significantly for the samples fabricated by this novel method. The effects of the sintering temperature, forming pressure, and polymer content on the physical and mechanical properties of the final porous ceramic were also evaluated in this study. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131 , 40425.
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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 | 0.001 |
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".