Accelerated Weathering and Carbonation (Mild to Intensified) of Natural Canadian Silicates (Kimberlite and Wollastonite) for CO2 Sequestration
Bibliographic record
Abstract
Canada’s mineral reserves can play a very important role in curbing climate change if natural alkaline minerals are used for the process of mineral carbonation. In this work, the potential of using two Canadian natural silicates for accelerated carbonation is experimentally assessed: kimberlite mine tailing (Mg0.846Al0.165Fe0.147Ca0.067SiO3.381) from the Northwest Territories, and mined wollastonite ore (Ca0.609Mg0.132Al0.091Fe0.024SiO2.914) from Ontario. The aim of this work was to evaluate the weathering reactivity and CO2 uptake capacity via carbonation of these two comminuted rocks, both of which are made up of a mixture of alkaline minerals, under process conditions that spanned from milder to intensified. Research questions addressed include: does kimberlite contain a sufficient amount of reactive minerals to act as an effective carbon sink; is dehydroxylation necessary to activate kimberlite, and to what extent does it do this; do secondary phases of wollastonite hinder its reactivity; and can either of these minerals be carbonated without pH buffering, or only weathered? Incubator, slurry, and pressurized slurry methods of accelerated weathering and carbonation were used, and the effect of the process parameters (temperature, solid-to-liquid ration, reaction time, CO2 level, pH buffer) on the CO2 uptake and crystalline carbonates formation is tested. The reacted samples were analyzed by pH test, loss-on-ignition test, calcimeter test, and X-ray diffraction analysis. Results showed that wollastonite ore (rich in fast-weathering CaSiO3) is more suitable for accelerated carbonation than kimberlite tailing (containing slow-weathering hydrated magnesium silicates and aluminosilicates) when only its capability to rapidly form solid carbonates is considered. Incubator and pressurized buffered slurry methods proved to be most effective as under these conditions the precipitation of carbonates was more favorable, while the unbuffered slurry reaction conditions were more akin to accelerated weathering rather than accelerated carbonation.
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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 | 0.001 | 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) | 0.001 | 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".