Intensified mineral carbonation of natural Canadian silicates using simultaneous ball milling
Bibliographic record
Abstract
Carbon concentrations in the atmosphere are increasing yearly, making it the primary contributor to climate change. To reduce CO 2 emissions, various strategies and technologies have been implemented. Mineral carbonation is an effective technology for mitigating climate change. Despite its efficiency, the slow pace of mineral carbonation poses a challenge when paired with the rate of emissions from point sources such as industrial facilities. To address this, the research focuses on studying mineral carbonation under mechanically and chemically intensified conditions. The project investigated the simultaneous ball milling and carbonation of Ca- and Mg-hydroxides and natural Canadian silicates (kimberlite and wollastonite) using a Retsch GrindControl jar reactor. Three additives (NaOH, MgCl 2 , and CH 3 CH 2 OH) were examined for their potential to enhance carbonation efficiency and reaction rate and to control carbonate mineralogy . In-situ temperature measurement enabled tracking milling and exothermic carbonation heat generation. Characterization techniques to gain insight into the reaction and products included pH testing, calcimetry, XRD analysis , and SEM imaging. For most feedstocks , water as the main solvent led to higher carbonation and precipitating of different carbonates (hydromagnesite, aragonite , calcite), while for kimberlite , using NaOH's pH buffering led to better performance. Ball-milling was shown to assist in intensifying mineral carbonation reactions by integrating milling and reaction unit processes into one, whereby the reactive surface area is increased at the right time (i.e., as passivation is about to initiate). Results indicate up to 5 and 15.7 times net increase in the carbonation content of studied silicates and hydroxides, respectively. Still, as planetary ball mills are designed primarily for comminution rather than multi-phase (gas-liquid-solid) mixing, further research is needed to identify if the gas-paste mixing efficiency achieved could be a limiting factor calling for other types of milling equipment for this application.
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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) | 0.001 | 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 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".