Properties of Alkali Activated Slag Concrete Incorporating Waste Materials as Aggregate: A Review
Bibliographic record
Abstract
Alkali activated slag (AAS) has gained huge attention in recent years due to its ability to replace ordinary Portland cement (OPC) as a binder in concrete. A need to replace OPC is imminent due to the high carbon dioxide emitted into the environment during its production. However, the use of this type of binder did not eliminate the huge strain placed on the deposit of natural resources. With the demand for concrete predicted to rise significantly in coming years, this means there will be a consequential increase in the amount of natural deposits of aggregates exploited, as aggregates make up about 80% by the volume of concrete. Therefore, in order to meet this forthcoming demand of sustainable concrete, and reduce the excessive strain on the use of natural aggregates, it is essential to find alternative materials that can be used as aggregate in concrete using AAS as a binder. This paper summarizes experimental results from various studies on the use of waste materials on aggregate. The fresh and hardened properties, alongside the cost and sustainability indications, are explored. It was drawn from this review that more reduction in carbon dioxide emission and cost could be achieved with the use of waste materials as aggregate in concrete. In addition, concrete made with AAS as a binder and incorporating waste as aggregate showed similar/higher properties with those made with natural aggregate. However, proper selection of types of wastes and replacement levels of these waste materials used as aggregate is still required to achieve enhanced properties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".