Calcined Palygorskites as Supplementary Cementitious Materials
Bibliographic record
Abstract
Abstract Reducing the environmental footprint of cement is an absolute necessity to meet the commitments of COP26 and to limit global warming to + 1.5°C compared to the pre-industrial level. In this context, particular interest has developed in recent years in the use of calcined clays as supplementary cementitious materials (SCMs). Due to their high reactivity, large reserves and homogeneous distribution on the earth's surface, calcined clays represent a viable alternative to conventional SCMs. Clay minerals are highly variable and numerous, each with their own characteristics. As a result, not all of them have potential for use as SCMs. The present paper investigated the use of palygorskite (a clay that has been relatively poorly studied) as an SCM. Two commercial palygorskites of different grades were selected and their calcination was studied by X-ray diffraction and pozzolanic activity tests. Blended cements incorporating 20% of each calcined palygorskite were prepared and the mechanical performance and resistivity of the mortars measured. The results show that the optimum calcination temperature is 800°C (allowing complete amorphization of the clay fraction and the highest pozzolanic reactivity) for both clays. Mortars made with 80% ordinary Portland cement (OPC) blended with 20% of 800°C calcined palygorskite allowed a significant increase in compressive strength and electrical resistivity compared to the reference (100% OPC). The clay sample with palygorskite as the dominant mineral exhibited the greatest pozzolanic reactivity and mechanical performance in cementitious systems, confirming that palygorskite is a clay mineral with a significant potential for a use as a SCM. The second sample with smaller palygorskite content also allowed a significant increase in mechanical performance. This demonstrated that it is not necessary to use high-purity samples and enhances the value of this type of material.
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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) | 0.059 | 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".