Effect of Cenosphere Fly Ash on the Thermal, Mechanical, and Morphological Properties of Rigid PVC Foam Composites
Bibliographic record
Abstract
Cenosphere fly ash is a byproduct of coal combustion processes of power plants. It is composed of hollow, hard shelled, minute spheres, which are made up of silica, iron, and alumina. In this study, cenosphere fly ash is incorporated into rigid PVC foam to improve thermal and mechanical properties of their composites. Microstructural, physical, mechanical, and thermal properties of rigid PVC foam extruded with different loadings of cenosphere fly ash (6, 12, 18phr) are characterized. The measured density of the extruded PVC foam composites increased with cenosphere content, indicating a hindrance to the foaming process. Tensile and flexural mechanical properties improved at higher cenosphere content, while the impact strength decreased at initial loading of 6 phr of cenosphere particles and remained steady at higher loadings. Thermal characterization of the extruded samples showed that glass transition temperature remained almost unaffected, while TGA analysis revealed no change in the initial degradation temperature and significant improvement in the final degradation temperature. Thermo-mechanical properties measured by DMA revealed a remarkable improvement in the viscoelastic properties of the composites reinforced with cenosphere particles. SEM analysis of the composites microstructure confirmed that the cenosphere particles were mechanically interlocked with good interfacial interaction in the PVC matrix.
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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 | 0.000 |
| 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".