Effect of the type of superplasticizer on the properties of cementitious systems incorporating slag
Bibliographic record
Abstract
Superplasticizers have become an integral ingredient in the formulation of concretes. After 40 years, their use and dosage remain uncertain due to variations in their compositions and those of cement. In addition, the substitution of cement by supplementary cementitious materials having different chemical compositions exacerbates the problem without counting the multiplicity of superplasticizers to choose from. The present work consists of a study of the rheological and mechanical properties of cementitious systems containing slag and various types of superplasticizers. The tests were carried out on pastes, mortars and concretes incorporating slag in partial cement replacement and four superplasticizers types, polynaphthalene sulphonate (PNS) and three polycarboxylates (PC). The results of this study demonstrate that the viscosity and the yield stress increase with the rate of incorporation of the slag. The air increases with the polycarboxylates but this effect is less perceptible in the presence of the slag. Polycarboxylates improve workability more than PNS. The use of polycarboxylates reduces the viscosity and the yield stress. The compressive strength of concretes containing slag is low at early age but high at long run. They exhibit good resistances to scaling. The permeability to chloride ions is considerably reduced in the presence of the slag independently of the type of superplasticizer, suggesting good durability of these concretes in potentially aggressive external environments.
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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 | 0.001 |
| 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) | 0.002 | 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".