Steam Reactivation of Partially Utilized Limestone Sulfur Sorbents
Bibliographic record
Abstract
A novel dual-environment thermogravimetric reactor was used to evaluate the steam reactivation of three limestones having differing sulfation morphologies. A clear correlation was observed between the morphology of the limestones and the ability of steam to reactivate "fully sulfated" sorbents. Unreacted core particles led to the highest conversion of CaO to Ca(OH)2 and the highest increase in Ca utilization (40%), followed by network sulfating limestone particles (9%). Virtually no hydration or reactivation was observed for uniformly sulfated particles. Steam hydration of an unreacted core sulfating limestone showed a decrease in reactivation with increasing temperature in the range 250 to 500°C. However, there was no clear correlation between CaO to Ca(OH)2 conversion and the extent of reactivation, likely due to changes in the rate-limiting resistance. At 500°C, Ca(OH)2 is unstable, resulting in no transformation of CaO and no reactivation. Reduced levels of hydration and reactivation at 450°C, compared to lower temperatures, is believed to result from the reaction rate exceeding the diffusion rate, leading to a plugged Ca(OH)2 product layer preventing further hydration, or a combined effect of smaller micropores and lower steam partial pressure inside the particles. Similar levels of hydration, but variations in reactivation, at 250 to 400°C are attributed to the effect of faster evolution of gas when particles are heated more quickly.
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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".