Synthesis and characterization of eco-friendly mortars made with RHA-NaOH activated fly ash as binder at room temperature
Bibliographic record
Abstract
In this study, an ecofriendly binder was developed by using rice husk ash (RHA) and sodium hydroxide as the activator alongside fly ash (FA) as the aluminosilicate precursor at ambient conditions. The developed binder was used in the production of mortars with varying proportions of sand. A total of three mortar mixtures were developed with sand to binder ratios of 0.55, 0.83 and 1.11. The corresponding behaviour of the mortars and influence of the sand proportions was assessed in terms of the compressive strength, water absorption, density, porosity. Microstructural investigations such as scanning electron microscopy, energy dispersive x-ray spectroscopy, infrared spectrum analysis and mercury intrusion porosimetry were also used to validate the physical properties. The findings from this study demonstrated that RHA can be used successfully as an activator component in the production of mortars. In terms of the sand content, it was found out that increasing the sand to binder ratio has detrimental effects on the performance of the mortars due to the reduction in the binder content primarily. The microstructure analysis of the mortars made with sand to binder ratio of 0.55 showed a compact and strong structure justifying the higher compressive strength achieved. The MIP analysis confirmed that the formation of C-A-S-H gel at the advanced ages allowed the pores refinement with a significant decrease in the fraction of the capillary and macroscopic pores within the geopolymer mortars.
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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 | 0.001 | 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 | 0.001 |
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; 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".