CO<sub>2</sub> Capture with Mg-, Al-, and Zr- Assisted CaO-Based Sorbents in the Calcium Looping Process Under Mild and Realistic Conditions
Bibliographic record
Abstract
The calcium looping (CaL) process is a promising carbon capture technology for CO 2 capture from point source emitters. A key challenge in the CaL process is the loss of sorbent capacity over successive capture-regeneration cycles due to sintering, which affects long-term stability. This study addresses this issue by a novel approach of incorporating MgO, Al 2 O 3, and ZrO 2 as promoters into calcium-based sorbents synthesized using the solution combustion synthesis (SCS) method. Sorbents were developed in mono-, bi-, and trimetallic configurations using soluble metal nitrates as precursors. Among the tested sorbents, Ca/(Zr–Al) demonstrated the highest CO 2 uptake of 0.46 g of CO 2 /g of sorbent, while Ca/(Mg–Zr–Al) achieved 0.43 g of CO 2 /g of sorbent. Both configurations exhibited exceptional stability, maintaining over 90% of their initial capacity after 50 cycles at elevated temperatures. These results highlight the effectiveness of bi- and trimetallic sorbents in enhancing the performance and durability of the CaL process.
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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".