Characterization, reactivity and rheological behaviour of metakaolin and Meta-halloysite based geopolymer binders
Bibliographic record
Abstract
The type of aluminosilicate precursor used in the synthesis of geopolymer binders plays a huge role in the resulting performance. Thus, it is critical to understand the properties of precursors and how they influence the corresponding performance of geopolymer binders. In this study, metakaolin and meta halloysite are used as the aluminosilicate precursor in the synthesis of geopolymer binders. These precursors are obtained locally in order to propel the sustainable development and application of geopolymers. The precursors were characterized and the corresponding influence on the reactivity, rheology and setting times of geopolymers was investigated. In addition to the influence of precursor type on the properties of the geopolymers, the effect of two silica moduli (i.e. 1.3 and 1.5) was also evaluated. The results from this study indicated that increasing the activator silica modulus from 1.3 to 1.5 extended the setting times and increased the stress strain of the geopolymer binders. Characterization of the precursors indicated that metakaolin has a higher amorphous content compared to that of meta halloysite. However, the finer particles of meta halloysite embodied it with the ability to participate in a faster geopolymerization and result in more formation of activation products.
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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 | 0.000 |
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".