Maximizing carbon uptake and performance gain in slag-containing concretes through early carbonation
Bibliographic record
Abstract
Carbon dioxide (CO2) emissions have been identified as a major contributor to climate change. Current CO2 mitigation efforts focus on the removal, recovery and disposal of CO2 at point sources. Finding beneficial uses of as-captured or recovered CO2 is a critical challenge in greenhouse gas mitigation. This thesis investigates the possibility of the beneficial use of carbon dioxide in precast concrete production and the performance, both short-term and long-term, of the concretes so produced. The calcium compounds in cementitious materials react readily with carbon dioxide to convert CO2 to thermodynamically stable carbonates. The reaction accelerates strength development and makes the technology appropriate for early age curing. Paste, mortar and concrete samples were examined to quantify such aspects as the carbon dioxide uptake, strength development, and durability of carbonated concrete. It was found that the uptake by the cementitious binders was significant. Compared to their theoretical capacity, cement could reach a carbonation degree of over 25% when treated as pastes and about 20% when used as a part of concrete. The study compared carbonation-cured and hydrated Portland cement concrete and slag cement concretes in terms of their early strength, late strength, weathering carbonation shrinkage, freeze/thaw durability, water absorption, and pH. The carbonated concrete was generally comparable, or superior, to the hydrated concrete except for the case of a 50% GGBF slag blend which had a slower strength development due to reduced secondary cementitious reaction. A second method of binding carbon into concrete was considered by carbonating ladle slag fines and us
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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) | 0.000 | 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) | 0.001 | 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".