Repurposing waste pozzolans for cleaner mortar production: mechanical and durability properties with microstructural behavior
Bibliographic record
Abstract
This study investigates the potential of three waste-derived supplementary cementitious materials (SCMs)—volcanic ash (VA), eggshell (ES), and rice husk ash (RHA)—as partial replacements for ordinary Portland cement (OPC) in mortar. Mortar mixes with 0%, 5%, 10%, 15%, and 20% replacement levels were evaluated in terms of fresh, mechanical, and durability properties, along with high-temperature performance, failure modes, microstructural characteristics, and cost analysis. The results demonstrated that a 5% replacement of OPC with VA and RHA enhanced compressive strength by 8.2% and 7%, respectively, while ES achieved a 16% increase at a 10% replacement. However, exposure to elevated temperatures led to compressive strength reductions of up to 87%. Flexural strength improvements were observed, with increases of 15% for VA, 43% for ES, and 21% for RHA. Economically, incorporating 20% VA, ES, and RHA led to cost reductions of 1.2%, 7.4%, and 2.5%, respectively. Additionally, the strength-to-CO2 ratio increased up to 11.4%, 22.0%, and 8.3% for VA, ES, and RHA-based mortars, respectively, compared to conventional OPC mortar. All SCMs met ASTM C618-22 criteria for natural pozzolans, with optimal replacement levels determined as 5% for VA, 10% for ES, and 5% for RHA. This study underscores the eco-friendly potential of waste-derived SCMs in producing sustainable mortar while reducing cement consumption, costs, and environmental impact.
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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 | 0.000 |
| 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".