Experimental study and classification of natural zeolite pozzolan for cement in South Africa
Bibliographic record
Abstract
The present study investigated the performance of South African natural zeolite for potential use as a cement extender. To the best knowledge of the authors, the natural zeolite studied has not been employed before as pozzolan in the cement industry, and its proposed use would be new in concrete construction. In the investigation, mortar mixtures were prepared using ordinary Portland cement CEM I 52,5N blended with 0, 10, 20 and 30% natural zeolite. The effectiveness of natural zeolite was also compared with performance results of mixtures containing 30% fly ash. The tests conducted were workability, compressive strength, pozzolanic activity with lime, drying shrinkage, alkali-silica reaction, and sulphate resistance. Analytical studies were done using X-ray diffraction and scanning electron microscopy coupled with energy dispersive spectroscopy. It was found that, while incorporation of natural zeolite in cement reduces workability, its effects on mechanical properties and on durability characteristics were superior to those of fly ash, as the former effectively enhanced long-term strength and mitigated drying shrinkage, alkali-silica reaction and sulphate attack. Incorporation of 20% natural zeolite in cement gave an effective overall performance, meeting the ASTM C618 (2015) criteria for Class N pozzolan. Based on EN 197-1 (2000) / SANS 50197-1 (2013), the blend of natural zeolite and ordinary Portland cement met the criteria for its classification as CEM II/A-P 32.5N,R cement type.
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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 | 0.001 | 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".