Mitigating of drying shrinkage in alkali-activated slag composites
Bibliographic record
Abstract
Abstract Alkali activated slag composites are promising alternatives to be used as a replacement of Portland cement composites for different construction applications. However, despite the evolution of these composites over the years, its high drying shrinkage still poses a limitation on its application. The increasing interest in alkali-activated slag composites by the research community has resulted in the use of various methods and materials to mitigate the drying shrinkage. This current paper explores the different major types of mitigation techniques that can be used to reduce the drying shrinkage in alkali-activated composites. The mitigation techniques explored are in terms of the use of various materials and curing methods. Discussions presented in this paper showed that a significant reduction in the drying shrinkage can be achieved by partially replacing slag with mineral admixtures or incorporating chemical admixtures specifically made to reduce shrinkage. The use of appropriate internal or external curing method for alkali-activated slag was also found to reduce drying shrinkage effectively. However, it is recommended to carry out further research in order to fully understand the mechanism of drying shrinkage in alkali-activated slag composites in order to develop effective ways to mitigate it.
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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".