Study on Carbonation of Ultramafic Tailings
Bibliographic record
Abstract
As global industrialization leads to an increase in atmospheric CO₂ concentration, causing environmental issues, reducing CO₂ emissions has become a consensus. CO₂mineralization storage technology has garnered attention, with ultrabasic tailings being ideal raw materials due to their rich content of magnesium, iron, and other elements. This study centers on the carbonation of ultrabasic tailings, investigating its kinetic mechanisms and optimizing conditions. The research framework encompasses the kinetics of direct aqueous carbonation of olivine under a CO₂ partial pressure of 6.5 MPa, the mechanism of mechanical activation of multiphase ultrabasic tailings, and the feasibility study of ultrabasic mine exploitation in conjunction with CO₂ mineralization storage technology. In terms of research methods, olivine from Washington State, USA, and tailings from northern British Columbia, Canada, were selected as materials. Experiments were carried out using a stirred autoclave manufactured by Parr Instrument Company (USA), with additional equipment such as a laser diffraction particle size analyzer employed for characterization purposes. Quantitative analysis of product composition and chemical kinetic theory were used to analyze the reaction. The research results show that optimizing conditions under low CO₂ partial pressure can significantly enhance the degree of olivine carbonation, and mechanical activation can increase the reactivity of minerals, providing theoretical support for the promotion of ultrabasic mine exploitation in conjunction with CO₂ mineralization storage technology
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".