Performance evaluation of foaming agents in cellular concrete based on foamed alkali-activated slag
Bibliographic record
Abstract
In this work, three different foaming agents were selected and their performance on density, compressive strength, pore structure, and molecular structure of alkali-activated blast furnace slag cellular concrete have been investigated. For this purpose, pre-formed foams based on sodium lauryl sulfate, protein-based foaming agent, and hydrogen peroxide were added to the alkali-activated slag paste with determined activator composition. After curing, density and compressive strength of cellular concretes were evaluated. Also, macroscopic pore size distribution was investigated by image processing technique for studying its relation with density and compressive strength. Results showed that with increasing the amount of foam, the density and the compressive strength decreased due to increases in both the number of pores per area and the pore average size. Samples containing protein-based foam showed higher mechanical strength, which could be due to its effect on the molecular structure of hydration product resulting in a stronger bond and hence higher compressive strength.
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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 | 0.001 | 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 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".