Core-in-Shell CaO/CuO-Based Composite for CO<sub>2</sub> Capture
Bibliographic record
Abstract
This paper describes the preparation of composite materials containing both CaO as a reversible CO 2 sorbent and CuO, serving as an oxygen carrier, which allows the spent Ca sorbent to be regenerated in a fuel gas stream after it has been used for CO 2 capture. Calcium aluminate cement is used as a support to enhance pellet strength. The pellets were prepared in a mechanical pelletizer for granulation of powdered materials with addition of spray water. Three types of pellets were prepared: (i) core-in-shell with 50% CuO and 50% CaO (75% CuO and 25% CaO in the core), (ii) core-in-shell with 50% CuO, 40% CaO, and 10% cement (75% CuO and 25% CaO in the core), and (iii) homogeneous pellets with 50% CuO, 40% CaO, and 10% cement addition as a binder. CO 2 /O 2 carrying activity of the pellets was then tested in a thermogravimetric analyzer (TGA). The attrition resistance of the obtained material was examined during attrition tests in a bubbling fluidized bed (i.d. 50 mm). The oxygen carrying capacity of pellets indicates that 25% CaO in the core is sufficient to support the CuO and prevent decay of its activity as an oxygen carrier during reduction/oxidation cycles. To demonstrate that the pellets produced actually have a core-in-shell pattern, larger cross-sectioned particles were analyzed using the scanning electron microscope/energy dispersive X-ray method (SEM/EDX). The SEM/EDX analyses clearly showed different morphology and elemental composition of the core and shell, with a higher content of CuO in the core. The results of attrition tests showed that after fluidization for 2 h, particle size distribution changed negligibly and high temperature did not cause significantly more pronounced attrition. These tests clearly showed that the procedure employed is suitable for large-scale preparation of core-in-shell CaO/CuO-based pellets which have numerous benefits.
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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".