Weathering and cementation of historic kimberlite residues from South Africa: Implications for residue stabilization and CO2 sequestration
Bibliographic record
Abstract
Enhanced weathering and carbon dioxide (CO 2 ) mineralization of ultramafic mine wastes, including kimberlite residues from diamond mining, provides secure storage of this greenhouse gas and may physically stabilize mine impoundments. Yet, the outcomes of these processes over extensive periods (i.e., decades) remain relatively unknown. This study examined coarse residues from historic impoundments at the Cullinan and Voorspoed diamond mines in South Africa that have weathered over 50 to more than 100 years to investigate weathering and cementation pathways. Cemented residues ( n = 7) were mainly composed of lizardite (9.6–43.2 wt.%), saponite (10.2–34.7 wt.%), and augite (6.6–27.8 wt.%), and had minor abundances of calcite (1.7–8.8 wt.%). Electron microscopy and Raman spectroscopy revealed that three plausible pathways contributed to cementing residues: (1) secondary clay precipitation, (2) carbonate precipitation and recycling, and (3) particle entrainment and infilling. Quantitative mineralogical analyses of the cement (<63 μm) and clast (>63 μm) fractions showed that the abundances of most minerals were similar between fractions, indicating that infilling of pore spaces with fine-grained particles contributed substantially to residue cementation. Stable and radiogenic carbon isotope ( 13 C, 14 C) analyses of carbonates indicated limited incorporation of organic matter and atmospheric CO 2 , an indication of surface weathering. Residue cementation led to some strength development (unconfined compressive strengths = 0.1–0.2 MPa), demonstrating the potential for mineral weathering to stabilize mine residues without chemical additives. Modifying residue management practices during the operational, closure, and reclamation phases at Cullinan, Voorspoed, and other mines, such as through residue co-disposal or implementing enhanced weathering practices, may improve residue stabilization and CO 2 sequestration..
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".