Improved Long-Term Conversion of Limestone-Derived Sorbents for In Situ Capture of CO<sub>2</sub> in a Fluidized Bed Combustor
Bibliographic record
Abstract
Cyclic carbonation and calcination reactions were investigated for capturing CO 2 from combustion and gasification processes. Sorbent particles in the size range 600−1400 μm were subjected to multiple capture cycles at atmospheric pressure to obtain a surface mapping of conversion based on calcination and carbonation temperatures. Steam hydration of CaO was utilized to increase both pore area and pore volume to improve long-term conversion to CaCO 3 over multiple cycles. The steam hydration improved the long-term performance of the sorbent, resulting in directly measured conversions as high as 52% and estimated conversions as high as 59% after up to 20 cycles. It is estimated that the increase in conversion has improved the economics of the proposed process to the point where commercialization is attractive. It has been shown that when carbonating in the temperature range from 700 to 740 °C, calcination temperatures from 700 to 900 °C can be used without seriously reducing the conversion of CaO for CO 2 capture over multiple cycles. Processes based on this approach are expected to be able to reduce CO 2 emissions from coal- and petroleum coke-fired fluidized bed combustors by up to 85%, while avoiding excessive sorbent replacement.
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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".