Activation of slag through a combination of NaOH/NaS alkali for transforming it into geopolymer slag binder mortar – assessment the effects of two different Blaine fines and three different curing conditions
Bibliographic record
Abstract
This study investigates the effects of two different Blaine fineness and three distinct curing conditions on the physico-mechanical properties of a geopolymer-ground granulated blast furnace slag (GGBFS) binder mortar activated through a combination of NaOH/NaS alkalis. By ensuring constant curing and mixing conditions, geopolymer mortar (GPM) specimens were prepared and evaluated to determine their capillary water sorption, capillarity coefficient, and change in unit weight, alongside their compressive strength and flexural strength 3, 7, 28, and 56 d after production. It was found that the capillary water sorption decreased by approximately 50% as the curing temperature of the water increased from ambient temperature to 22 °C. The coefficient of capillarity remained constant across the geopolymer materials, irrespective of the Blaine fineness of the GGBFS. Furthermore, the increase in the unit weight, owing to the variation in the Blaine fineness of GGBFS, results in a reduction in the water sorption properties of GPMs. The GGBFS and alkali-based binders imparted a continuous increase in the compressive and flexural strengths. The results revealed that a Blaine fineness of 6000 cm2/g in the GGBFS under water-curing conditions imparted the most significant advantageous effect on the physico-mechanical properties of a GGBFS binder mortar activated through a combination of NaOH/NaS alkalis.
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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".