Pelletizing and Coating of Synthetic Zirconia Stabilized Calcium-Based Sorbents for Application in Calcium Looping CO<sub>2</sub> Capture
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Calcium oxide (CaO) has been investigated as a high-temperature performance sorption material for carbon capture due to its high carbon dioxide (CO 2 ) capacity, low cost, and environmental benignity. Unfortunately, commercialized application of CaO materials has been hindered by severe capacity loss during cycling operations. In an attempt to overcome these problems, this study investigated the effects of adding zirconia-based ceramic dopants and coating sorbents with highly crystalline zirconium dioxide (ZrO 2 ) layers derived from the hydrolysis of zirconium butoxide to control the growth of ZrO 2 crystals. Uncoated natural Cadomin delivered a high CO 2 capture capacity of more than 13 mol CO 2 /kg, while the zirconia-coated sorbents showed excellent cycling stability corresponding to a maximum capacity of retention of 79% after 21 cycles at high temperatures. More importantly, the highly crystalline ZrO 2 -coated sorbents doped by zirconia-based sorbents exhibited a significantly lower decay capacity compared to the uncoated sorbents, which could be attributed to the formation of a perovskite structure that is resistant at high temperatures and a high-temperature-resistant ceramic layer through the solid-state reaction of the highly mesoporous crystalline ZrO 2 layer with CaO. These results shed light on the development of sorbents with special structures and superior chemical and mechanical properties for high-performance calcium looping or regenerative calcium cycle processes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it