Comparison of innovative nano fly ash with conventional fly ash and nano-silica
Bibliographic record
Abstract
This report is an experimental study on the nano-powdering of fly ash and the improvement of cement performance by nano fly ash. Mortars with nano fly ash or nano-silica produced by a physical method are compared with mortar without a nano-binder. Mortar with nano-silica showed rapid setting. However, mortar with fly ash or nano fly ash exhibited delayed setting. The smaller the particle sizes, the higher is the compressive strength, demonstrating that mortar with nano fly ash shows superior performance with higher compressive strength from the beginning. Durability assessments revealed that chloride penetration resistance increased by 70% for mortar with nano fly ash or nano-silica. This shows that mortar with a smaller particle binder has excellent carbonation resistance. Nano-powdering effectively enhances the activation of a pozzolanic reaction and provides densely charged effects. These changes solve the problem of initial strength reduction — the greatest weakness of fly ash.
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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".