Ex Situ Carbon Mineralization for CO2 Capture Using Industrial Alkaline Wastes—Optimization and Future Prospects: A Review
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
Carbon mineralization has attracted great interest as a promising strategy to achieve a decarbonized pathway by 2050. Despite the significant environmental and economic promise associated with using industrial solid waste for carbon mineralization, the scale-up application of this approach is limited due to its low reactivity and relatively high cost. A clear understanding of the detailed mechanisms governing various carbonation techniques is needed to achieve high CO2 conversion efficiency. This review can provide valuable insight into carbon mineralization pathways, advantages and challenges, and potential feedstocks. Factors affecting reaction kinetics, and thereby carbonation efficiency, are also discussed. Then, we focus on the research progress of the most representative industrial solid wastes for CO2 mineralization, process conditions, and their carbonation potential. Lastly, a market analysis of the precipitated carbonate products is provided to assess economic feasibility for practical applications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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