Migration of transition metals and potential for carbon mineralization during acid leaching of processed kimberlite from Venetia diamond mine, South Africa
Bibliographic record
Abstract
Carbonation of mafic and ultramafic rocks and mineral wastes provides a permanent way to sequester excess atmospheric CO2. Recent research has shown that this method also offers the potential for enhanced recovery of critical metals from mine tailings. In this study, processed kimberlite from the Venetia diamond mine (South Africa) was used in column acid leaching experiments to assess both its carbonation potential and whether critical metals such as nickel could be recovered during mineral carbonation. Processed kimberlite was treated daily with one pore volume of either deionized water or dilute hydrochloric acid (0.04 M, 0.08 M, 0.12 M and 0.16 M) for 28 days. Iron-rich yellow precipitates consistent with yellow ground formed during the experiments both at the top of the residue columns (corresponding to the inlets of the columns) and within the leachates collected from the bases of columns. The carbonation potential and mobility of transition metals were investigated using a combination of quantitative X-ray diffraction (XRD) using Rietveld refinements, inductively coupled plasma mass spectrometry (ICP-MS), scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDXS), transmission electron microscopy (TEM) coupled with EDXS, and synchrotron-based X-ray fluorescence microscopy (XFM). Our results show that the high proportion of clay minerals (e.g., lizardite, smectite, talc, chlorite) in the processed kimberlite act as the primary source for Mg and transition metals such as Ni; however, calcite dissolution is the main source for Ca. The amount of Mg and Ca extracted from processed kimberlite increases with HCl concentration. If acid leaching of processed kimberlite were used at Venetia, the amount of Mg leached from clay minerals would provide an estimated CO2 offset potential ranging from 2.1 to 15.8 % of the mine's total annual emissions. The leached Ca from silicate dissolution could also provide an estimated CO2 offset potential ranging from 2.1 to 8.1 % of the mine's total annual emissions. However, the amount of CO2 released by calcite dissolution during this process is equivalent to 2.1–14.3 % of total annual CO2 emissions at Venetia., thus resulting in a net estimated CO2 offset potential of 2.1–9.6 % if the Ca released from calcite could not be recarbonated. If all of the Ca could be reprecipitated as calcite, the acid leaching techniques employed in this study could offset 4.2–23.9 % of the Venetia mine's CO2 emissions. Ultimately, greater concentrations and/or amounts of acid may be used to access more of the offset potential of Mg phyllosilicates in kimberlite, but the CO2 released by calcite dissolution must also be won back by recarbonation.
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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".