Valorization of partially combusted wood fly ash with nano-silica as low-impact alternative to coal fly ash in cementitious composites
Bibliographic record
Abstract
The declining availability of coal fly ash (CFA) due to the phasing out of coal-fired power plants has created an urgent demand for alternative supplementary cementitious materials (SCMs) in sustainable concrete construction. This study aims to effectively recycle wood fly ash (WFA), a by-product from wood biomass combustion, as an SCM for greener construction practices. While WFA has demonstrated promising potential, its partially burnt nature negatively impacts mechanical properties due to the presence of porous biochars. This study explores the valorization of WFA as a low-carbon SCM through the addition of a small dosage of nano-silica (NS) to mitigate these drawbacks. Ternary-blended cementitious composites were prepared by replacing cement with 15 % and 30 % WFA, combined with 3 % NS, to evaluate fresh, mechanical, durability, and microstructural properties. The results were compared with composites made of commercially available classes C and F CFA. It was observed that although NS addition negatively affected the fresh properties, it greatly enhanced the mechanical properties, chloride resistance, water absorption, and freeze-thaw durability of the WFA-modified composites. The improved freeze-thaw resistance can potentially extend the service life, thereby enhancing environmental compatibility. The mix having 15 % WFA and 3 % NS outperformed the control one in both mechanical and durability aspects, indicating that a low-level NS replacement can effectively mitigate the drawbacks of partially combusted WFA. Overall, CFAs demonstrated better performance than WFA at the 30 % level. • Wood fly ash possesses good pozzolanic properties. • Nano-silica improves the strength and durability of wood fly ash-based composites. • The mix with 15 % wood fly ash and 3 % nano-silica outperforms the control one. • Overall, coal fly ash demonstrates better performance than wood fly ash.
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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 | 0.000 | 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) | 0.000 | 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".