Valorization of Kimberlite Tailings by Carbon Capture and Utilization (CCU) Method
Bibliographic record
Abstract
In the world of construction, cement plays a vital role, but despite its reputation and affordable prices, the cement industry faces multiple challenges due to pollution and sustainability concerns. This study aimed to assess the possibility of utilizing carbonated kimberlite tailings, a waste product from diamond mining, as a partial cement substitute in the preparation of concrete bricks. This is a unique opportunity to help close the gap between fundamental research in mineral carbonation and its industrial implementation to generate commercial products. Kimberlite was subjected to a mild thin-film carbonation process in a CO2 incubator at varying levels of CO2 concentration (10 vol% and 20 vol% at ambient pressure), kimberlite paste moisture content (10 wt% to 20 wt%), and chamber temperature (35 and 50 °C). The formation of magnesium carbonates, in the form of nesquehonite and lansfordite, was verified by X-ray diffraction analysis, and total CO2 uptake was quantified by thermal decomposition in furnace testing. Carbonated kimberlite tailings were then used to cast bricks. Replacement of cement between 10% and 20% were tested, with a constant water-to-binder ratio of 0.6:1, and a cementitious material-to-sand ratio of 1:3. Initial water absorption and 7- and 28-days compressive strength tests were carried out. The results obtained confirm the possibility of using carbonated kimberlite to replace cement partially, and highlight the benefits of carbonating the kimberlite for such application, and recommendations for future research are suggested. This study demonstrates the potential use of mining tailings to prototype the sequestration of CO2 into sustainable building materials to positively impact the increasing demand for cement-based products.
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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) | 0.001 | 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".