Influence of amorphous raw rice husk ash as precursor and curing condition on the performance of alkali activated concrete
Bibliographic record
Abstract
The detrimental impact of Portland cement (PC) which is the primary binder in the production of cementitious materials such as concrete has called for a need to use alternative binders to produce concrete. Of such promising sustainable alternative to the conventional PC concrete (PCC) are alkali-activated concrete (AACs) which are produced by using a binder composed of an aluminosilicate precursor and alkali activator. In this study, blast furnace slag (BFS) was used as the primary precursors in the production of AACs. Amorphous raw rice husk ash (RRHA) was used at various dosages to partially replace BFS as the precursor. The corresponding influence of the RRHA content and curing conditions on the performance of AACs were evaluated. The two curing conditions utilized are ambient temperature curing and thermal curing for 24 h at 60 °C followed by ambient temperature curing. Findings from this study showed that the use of RRHA as a 10% replacement of the BFS is optimum as it yielded enhanced mechanical and durability performance. It was also found out that the thermal curing of AACs for 24 h before curing at ambient temperature is beneficial to improving the performance.
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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".