CO<sub>2</sub> Sequestration Potential of Steel Slags at Ambient Pressure and Temperature
Bibliographic record
Abstract
A study of carbon dioxide sequestration has been performed in aqueous electric arc furnace (EAF) and ladle furnace (LF) slag suspensions, in leached hydrated-matrixes, and in leachates to estimate their intrinsic sequestration potential at ambient conditions (temperature of 20 ± 1 °C and atmospheric pressure). The CO 2 sequestration was tested in aqueous suspensions of steel slags at a liquid-to-solid ratio of 10 kg/kg as well as in leached hydrated-matrixes and leachates isolated from these fresh slag suspensions after three consecutive leachings. The sequestration assays were performed at 20 °C with a flow rate of 5 mL/min of a CO 2 concentration of 15.00 vol %. The results have revealed that the CO 2 sequestration capacity of the LF slag suspension (24.7 g of CO 2 /100 g of slag) is 14 times superior to that of the EAF slag suspension. This greater CO 2 sequestration capacity of the LF slag suspension may be associated in large part to its higher content of portlandite, which reacts with CO 2 relative to the EAF slag suspension. Moreover, the separation of hydrated-matrixes and leachates significantly enhanced the CO 2 sequestration capacity of EAF slag while a slight decrease was observed for the LF slags. This may be due to an obstruction of the CO 2 binding sites of LF slag hydrated-matrixes following the accumulation of calcium carbonate. Taken together, these results suggest that EAF and LF slags could be used for the CO 2 sequestration and given a good yield as well in aqueous suspension as in separated matrixes and leachates.
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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".