Process analysis of CO<sub>2</sub> capture from flue gas using carbonation/calcination cycles
Bibliographic record
Abstract
Abstract Process analysis of CO2 capture from flue gas using Ca‐based carbonation/calcination cycles is presented here. A carbonation/calcination system is composed essentially of two reactors (an absorber and a regenerator) with Ca‐based sorbent circulating between the two reactors (assumed here as fluidized beds). CO2 is, therefore, transferred from the absorber to the regenerator. Because of the endothermicity of the calcination reaction, a certain amount of coal is burned with pure oxygen in the regenerator. Detailed mass balance, heat balance and cost of electricity and CO2 mitigation for the carbonation/calcination cycles with three Ca‐based sorbents in dual fluidized beds were calculated and analyzed to study the effect of the Ca‐based sorbent activity decay on CO2 capture from flue gas. The three sorbents considered were: limestone, dolomite and CaO/Ca12Al14O33 (75/25 wt %) sorbent. All results, including the amount of coal and oxygen required, are presented with respect to the difference in calcium oxide conversion between the absorber and the regenerator, which is an important design parameter. Finally, costs of electricity and CO2 mitigation costs using carbonation/calcination cycles for the three sorbents were estimated. The results indicate that the economics of the carbonation/calcination process compare favorably with competing technologies for capturing CO2. © 2008 American Institute of Chemical Engineers AIChE J, 2008
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".