Carbonation Deactivation of Limestone in a Micro-Fluidized Bed Reactor
Bibliographic record
Abstract
Carbonation–calcination looping using CaO-based natural sorbents such as limestone is a promising technology for the capture of CO2 from fossil fuel-based power plants. In this study, the CO2 capture capacities of Buipe, Oterpkolu, and Nauli limestones from quarries in Ghana were measured in a laboratory-scale micro-fluidized bed reactor through multiple carbonation–calcination cycles. The changes in CO2 capture capacity and conversion with the number of cycles mostly correlated with the changes in the physico-chemical properties: Capture capacity dropped from >60% to <15% after 15 cycles and the surface area dropped to below 5 m2 g−1 from as much as 20 m2 g−1 (for the Oterkpolu). The pore volume of the Nauli limestone was essentially invariant with the number of cycles while it increased for the Buipe limestone, and initially increased and then dropped for the Oterpkolu limestone. This decrease was likely due to sintering and a reduction in the number of micropores. The unusual increase in pore volume after multiple cycles was due to the formation of mesopores with smaller pore diameters.
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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".