Carbonation-activated microstructural refinement in GUL-GGBFS blended mortars: Shrinkage mitigation and strength enhancement
Bibliographic record
Abstract
Carbonation curing, a potential method for achieving carbon-neutral concrete, enables cement-based materials to react with CO 2 and form stable carbonates. The objective of this study is to investigate the volume stability and microstructural changes of mortars exposed to drying (0.04 % ± 0.001 %) and accelerated carbonation (3 % ± 0.5 %). Five mixtures with general use limestone cement (GUL) and up to 80 % ground granulated blast furnace slag (GGBFS) replacement were analyzed. Macroscopic properties, including compressive strength and shrinkage, were assessed up to 174 days. Mineralogical composition was analyzed via X-ray diffraction (XRD) and thermogravimetric analysis (TG). Pore structures were investigated using X-ray computed tomography (XCT) and dynamic vapor sorption (DVS). Results indicate that 80 % GGBFS reduced 28-day compressive strength by 65.6 % compared to 0 % GGBFS under drying, while accelerated carbonation compensates for this reduction, increasing 46.9 % compressive strength as GGBFS rises from 0 % to 40 % due to pore refinement from calcite and dolomite formation. Accelerated carbonation increases shrinkage by 49.2 % in specimens with 0 % GGBFS, whereas incorporating over 40 % GGBFS reduced shrinkage by 20.3 %. Although carbonation densified the pore structure and limited CO 2 ingress, specimens with GGBFS showed higher carbonation rates attributed to the lower Ca(OH) 2 from cement dilution and pozzolanic reactions. XCT further revealed crack in high-GGBFS mixes (60 % and 80 %) after carbonation, which critically compromised their strength and durability. This study demonstrates that moderate GGBFS replacement combined with carbonation curing can improve strength and shrinkage resistance while advancing carbon-neutral construction.
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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".