Development of Zirconium-Stabilized Calcium Oxide Absorbent for Cyclic High-Temperature CO<sub>2</sub> Capture
Bibliographic record
Abstract
A high-temperature regenerable CO 2 absorbent, Zr-stabilized CaO, was prepared using the surfactant template-ultrasound synthesis method in this work. During 15 absorption/desorption cycles, it was found that Zr-stabilized CaO with a Zr/Ca molar ratio of 0.303 kept the most favorable stability and CO 2 uptake capacity among the proposed Zr-stabilized samples. During multiple carbonation/decarbonation cycles, the incorporation of zirconium inhibited the agglomeration and sintering of CaO particles, thereby improving the absorbent durability. The effects of carbonation temperature (600–700 °C) and surfactant amount used in the preparation method on the performance of the proposed absorbent were investigated. The results showed that an excess of surfactant negatively affects the absorbent structural stability. Multicycle CO 2 capture tests carried out between 600 and 700 °C showed that an increase in carbonation temperature improved the absorption capacity and durability of the proposed Zr-stabilized CaO absorbent. In summary, the results showed a superior prolonged stability of Zr-stabilized CaO as compared to pure CaO under severe operating conditions.
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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".