Drying Shrinkage, Sulphuric Acid and Sulphate Resistance of High-Volume Palm Oil Fuel Ash-Included Alkali-Activated Mortars
Bibliographic record
Abstract
Nowadays, an alkali-activated binder has become an emergent sustainable construction material as an alternative to traditional cement and geopolymer binders. However, high drying shrinkage and low durability performance in aggressive environments such as sulphuric acid and sulphate are the main problems of alkali-activated paste, mortar and concrete. Based on these factors, alkali-activated mortar (AAM) binders incorporating high-volume palm oil fuel ash (POFA), ground blast furnace slag (GBFS) and fly ash (FA) were designed to enhance their durability performance against aggressive environments. The compressive strength, drying shrinkage, loss in strength and weight, as well as the microstructures of these AAMs were evaluated after exposure to acid and sulphate solutions. Mortars made with a high volume of POFA showed an improved durability performance with reduced drying shrinkage compared to the control sample. Regarding the resistance against aggressive environments, AAMs with POFA content increasing from 0 to 70% showed a reduced loss in strength from 35 to 9% when subjected to an acid attack, respectively. Additionally, the results indicated that high-volume POFA binders with an increasing FA content as a GBFS replacement could improve the performance of the proposed mortars in terms of durability. It is asserted that POFA can significantly contribute to the cement-free industry, thus mitigating environmental problems such as carbon dioxide emission and landfill risks. Furthermore, the use of POFA can increase the lifespan of construction materials through a reduction in the deterioration resulting from shrinkage problems and aggressive environment attacks.
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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".