Electrical and Thermal Properties of Wollastonitebased Inorganic Phosphate Cement Modified with Fibres and Recycled Rubber Aggregates
Bibliographic record
Abstract
The use of fibres and recycled rubber aggregates to improve the fracture properties of wollastonite-based inorganic phosphate cement would have corresponding effects on the functional properties of the material.In this research, cement composites were designed to incorporate rubber aggregates (i.e.7.5-17.5 wt%), 1.5% volume fibre contents (i.e.macro polypropylene, amorphous metallic and carbon fibres), and a hybrid blend of both inert materials into the cement matrix.The electrical resistivity of the developed cement composites was measured using the Gamry device while their thermal conductivity was determined based on the guarded hot plate steady state method.It was found that the electrical resistivity of wollastonite-based inorganic phosphate cement increased with increasing curing age at room temperature.The incorporation of rubber aggregates into the cement matrix caused a significant increase and decrease in the electrical resistivity and thermal conductivity respectively, of cementitious composites formed.Meanwhile, as expected, the conductive fibres lowered the electrical resistivity and simultaneously increased the thermal conductivity of the inorganic cement.However, the polypropylene fibres increased both the electrical and thermal properties.Therefore, inert additives which have insulating properties (rubber aggregates and polypropylene fibre) favoured the production of cement composites with improved energy savings in buildings while the conductive (amorphous metallic and carbon) fibres can contribute to the material's smart potential.
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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".