Effect of Different Proportions of Fly Ash and GGBFS on the Compressive Strength of Geopolymer Mortar
Bibliographic record
Abstract
Nowadays, geopolymer plays a significant role in developing eco-friendly materials to avoid the pollution caused by the Portland cement industry. Geopolymer is a developed industrial by-product-based alternative concrete binder. The aim of this study to evaluate the effect of different proportions of Fly Ash (FA) and Ground Granulated Blast Furnace Slag (GGBFS) on the strength properties of geopolymer mortar. In this study, GGBFS was added as 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% of the total binder with NaOH concentrations 12 M and sodium silicate to sodium hydroxide ratio 2.5. The compressive strength was investigated experimentally in this study. The combination of FA and GGBFS were tested in a total of eleven geopolymer mix mortars, and the results show that combining the above constituents at 70℃ improves the compressive strength of geopolymer mortar. The result show that the mixture with 100% GGBFS replacement have maximum compressive strength (78.25 MPa) at 7-days age.
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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".