Sintering and Reactivity of CaCO3-Based Sorbents for In Situ CO2 Capture in Fluidized Beds under Realistic Calcination Conditions
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Bibliographic record
Abstract
Sintering during calcination/carbonation may introduce substantial economic penalties for a CO2 looping cycle using limestone/dolomite-derived sorbents. Here, cyclic carbonation and calcination reactions were investigated for CO2 capture under fluidized bed combustion (FBC) conditions. The cyclic carbonation characteristics of CaCO3-derived sorbents were compared at various calcination temperatures (700–925°C) and different gas stream compositions: pure N2 and a realistic calciner environment where high concentrations of CO2>80–90% (and the presence of SO2) are expected. The conditions during carbonation employed here were 700°C and 15% CO2 in N2 and 0.18% or 0.50% SO2 in selected tests, i.e., typically expected for a carbonator. Up to 20 calcination/carbonation cycles were conducted using a thermogravimetric analyzer (TGA) apparatus. Three Canadian limestones were tested: Kelly Rock, Havelock, and Cadomin, using a prescreened particle size range of 400–650μm. In addition, calcined Kelly Rock and Cadomin samples were hydrated by steam and examined. Sorbent reactivity was reduced whenever SO2 was introduced to either the calcining or carbonation streams. The multicyclic capture capacity of CaO for CO2 was substantially reduced at high concentrations of CO2 during the sorbent regeneration process and carbonation conversion of the Kelly Rock sample obtained after 20cycles was only 10.5%. Hydrated sorbents performed better for CO2 capture, but also showed significant deterioration following calcination in high CO2 gas streams. This indicates that high CO2 and SO2 levels in the gas stream lead to lower CaO conversion because of enhanced sintering and irreversible formation of CaSO4. Such effects can be reduced by separating sulfation and carbonation and by introducing steam to avoid extremely high CO2 atmospheres, albeit at a higher cost and/or increased engineering complexity.
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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 it