Comparison of thermal and mechanochemical activation for enhancing pozzolanic reactivity of illite-rich shale
Bibliographic record
Abstract
To address the challenges associated with urban construction waste disposal and promote sustainable construction practices, this study investigates the feasibility of repurposing an illite-rich waste shale as a supplementary cementitious material (SCM) through thermal and mechanochemical activation. The aim of this study is to develop a deeper understanding of the relationship between the chemical reactivity of activated shales and the performance of blended cement mortars. Various properties, including phase transitions, particle size distribution, surface morphology, chemical reactivity, as well as mortar fresh properties and compressive strength, were analyzed for the activated shales. The results show that the mechanochemically activated shale exhibited a noticeable increase in pozzolanic reactivity compared to the calcined shale. The mechanochemically activated shale also displayed a more granular surface morphology, which is beneficial for early-age reactivity. A bimodal particle size distribution was observed in the mechanochemically activated shale, likely attributed to the agglomeration of amorphized fine particles. Furthermore, the mechanochemically activated shale had a less negative impact on workability, primarily due to the re-adsorbed surface moisture, which offset the increased water demand in the blended cements. At 20 %, 30 %, and 40 % cement substitution levels, the mechanochemically activated shale mortar mixtures developed compressive strengths comparable to those of the control mixture at both 7 and 28 days. More importantly, the practical significance of this study lies in the successful activation of the illite-rich shale using an attrition mill for the first time, an industrially-scalable milling technology.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".