Comprehensive evaluation on the properties of blended cement containing calcined paper sludge
Bibliographic record
Abstract
Abstract This paper investigates the feasibility of exploiting paper sludge (PS) waste as partial cement replacement. Initially, PS was subjected to treatment by calcination to obtain paper sludge ash (PSA) followed by physical and chemical characterization. The influence of PSA inclusion at various cement replacement levels (5, 10, and 15% by weight) on cement properties was initially assessed. Next, the fresh properties, mechanical strengths, water transport, sulfate resistance, and drying shrinkage of blended cement mortars were observed and evaluated. Finally, the microstructure of selected blended cement pastes was observed through SEM–EDS, XRD, and TGA analysis. It was confirmed that using up to 15% of PSA complies with BS EN 196–3 requirements. The results also demonstrated that incorporation of up to 10% PSA was favourable as it has minimal influence on the consistency, early and late age, as well as residual strengths. Meanwhile, the filler effect of PSA imparted an improvement in drying shrinkage (> 7%), sulfate resistance (− 40%) as well as sorptivity when 5–10% of cement was replaced with PSA. While slight changes were observed from the diffractogram, both SEM–EDS and TGA–DSC analysis suggested that limited hydration occurred, hence PSA filler effect is more dominant. Overall, this study suggests limiting PSA incorporation in blended cement mortar mixtures up to 10% to attain adequate performance. Consequently, an eco-friendly blended cement can be produced with reduced cement usage while valorising waste streams from the paper industry simultaneously. Graphical abstract
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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".