Treatment and activation effects on kaolinite-based earth concrete
Bibliographic record
Abstract
Self-consolidating earth concrete (SCEC) addresses the long construction process of conventional earthen constructions and their structural limitations, while further efforts are needed to enhance its sustainability . This study explores the development of a kaolinite-based self-consolidating earth paste (SCEP) due to their blended powder system, incorporating raw and treated (calcined and ground-calcined) kaolinite under various activation techniques, such as water hydration, sodium hexametaphosphate (NaHMP), and sodium hydroxide (NaOH) activation. The synergistic effect of calcination and mechanosynthesis on rheological, mechanical, structural, and microstructural properties of SCEP were investigated. Mechanically treated kaolinite increased yield stress, plastic viscosity , storage modulus evolution, and build-up index, while delayed the strength development compared to the calcined kaolinite samples. Among the investigated activators, NaOH resulted in more promising structural build-up, storage modulus , and compressive strength development. These findings were elaborated with X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), calorimetry , thermogravimetric analysis (TGA), and scanning electron microscopy (SEM).
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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".