Using Belitic Calcium Sulfoaluminate Cement to Improve the Early-Age Strength of Limestone Calcined Clay Cement-Based Mixtures
Bibliographic record
Abstract
Limestone calcined clay cement (LC3) is a sustainable binder for reducing the cement industry’s carbon footprint. However, the low unconfined compressive strength (UCS) at early ages significantly hinders the further application of LC3. This paper aims to improve the UCS of LC3-based mixtures at early ages by blending them with belitic calcium sulfoaluminate (BCSA) cement. The study investigated how blending LC3 with BCSA cement at different contents (0%, 20%, 40%, 60%, 80%, and 100%) affects the mechanical performance (i.e., setting and UCS) of mixtures. Additionally, thermogravimetric analysis (TGA), X-ray diffraction (XRD), and scanning electron microscopy (SEM) were conducted to investigate the hydration characteristics of mixtures. The results indicate that BCSA cement significantly improved the UCS of LC3-based mortar at early ages. For example, at 2 h, the UCS of LC3-BCSA mortar containing 20% BCSA cement was 2.5 MPa, whereas LC3-based mortar barely gained UCS. Additionally, a lower substitution ratio of LC3 was conducive to achieving a higher UCS at later ages. LC3-BCSA mortar containing 20% BCSA cement achieved the highest 28-d UCS (48.4 MPa), which was 116.3% of that of LC3-based mortar and 128.0% of that of BCSA cement-based mortar. By contrast, LC3-BCSA mortar containing 80% BCSA cement obtained the lowest 28-d UCS. Moreover, LC3-BCSA mortar containing 20% BCSA cement exhibited the lowest CO2 intensity, which was only 89.0% of that of LC3-based mortar and 67.6% of that of BCSA cement-based mortar, demonstrating the enormous potential for effectively reducing carbon emissions in the cement industry.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".