Sustainable utilization of ultrafine rice husk ash in alkali activated concrete: Characterization and performance evaluation
Bibliographic record
Abstract
This paper investigates the novel effect of ultrafine rice husk ash (URHA) on the properties of alkali-activated concrete. Rice husk ash was obtained as waste from biomass energy production and further processed to obtain URHA. The URHA was first characterized using various techniques to understand its morphology, structure and chemical composition. The URHA was then used to replace fly ash in alkali-activated fly ash/slag concrete up to 10%, and the effects on the performance were evaluated. The optimum dosage of URHA was assessed based on the compressive strength and the resistance to chemical attacks was carried out on the control mixture and that incorporating the optimum URHA. Microstructural properties of some of the control mixture and that incorporating the optimum URHA content was also investigated. Results from this study showed that the use of URHA as a 5% replacement of the FA is optimum that ensured high performance.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".