Optimizing Precursors and Reagents for the Development of Alkali-Activated Binders in Ambient Curing Conditions
Why this work is in the frame
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Bibliographic record
Abstract
Alkali-activated binders (AABs) are developed through the activation of aluminosilicate-rich materials using alkaline reagents. The characteristics of AABs developed using a novel dry-mixing technique incorporating powder-based reagents/activators are extensively explored. A total of forty-four binder mixes are assessed in terms of their fresh and hardened state properties. The influence of mono/binary/ternary combinations of supplementary cementitious materials (SCMs)/precursors and different types/combinations/dosages of powder-based reagents on the strength and workability properties of different binder mixes are assessed to determine the optimum composition of precursors and the reagents. The binary (55% fly ash class C and 45% ground granulated blast furnace slag) and ternary (25% fly ash class C, 35% fly ash class F and 40% ground granulated blast furnace slag) binders with reagent-2 (calcium hydroxide and sodium sulfate = 2.5:1) exhibited desired workability and 28-day compressive strengths of 56 and 52 MPa, respectively. Microstructural analyses (in terms of SEM/EDS and XRD) revealed the formation of additional calcium aluminosilicate hydrate with sodium or mixed Ca/Na compounds in binary and ternary binders incorporating reagent-2, resulting in higher compressive strength. This research confirms the potential of producing powder-based cement-free green AABs incorporating binary/ternary combinations of SCMs having the desired fresh and hardened state properties under ambient curing conditions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it