CO<sub>2</sub> Carrying Behavior of Calcium Aluminate Pellets under High-Temperature/High-CO<sub>2</sub> Concentration Calcination Conditions
Bibliographic record
Abstract
Sintering and a resulting loss of activity during calcination/carbonation can introduce substantial economic penalties for a CO 2 looping cycle using CaO-based sorbents. In a real system, sorbent regeneration must be done at a high temperature to produce an almost pure CO 2 stream, and this will increase both sintering and loss of sorbent activity. The influence of severe calcination conditions on the CO 2 carrying behavior of calcium aluminate pellets is investigated here. Up to 30 calcination/carbonation cycles were performed using a thermogravimetric analyzer apparatus. The maximum temperature during the calcination stage in pure CO 2 was 950 °C, using different heating/cooling rates between two carbonation stages (700 °C, 20% CO 2 ). For comparison, cycles were also done using N 2 during the calcination stages. In addition, the original Cadomin limestone, used for pelletization, was also examined in its original form and the results obtained were compared with those for the aluminate pellets. As expected, high temperature during calcination strongly reduced CO 2 carrying capacities of both sorbents. However, aluminate pellets showed better resistance to these severe conditions. The conversion profiles obtained are significantly different to those obtained under milder conditions, with significant increased activity during the slower, diffusion-controlled, carbonation stage. Moreover, scanning electron microscopy analysis of samples after prolonged carbonation showed that pore filling occurred at the sorbent particle surfaces preventing diffusion of CO 2 toward the particle interior.
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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".