Galvanic sulphide oxidation as a metal-leaching mechanism and its environmental implications
Bibliographic record
Abstract
Following a brief review of the theoretical aspects of galvanic sulphide oxidation, the significance of galvanic interaction in the oxidation of natural mixed sulphide assemblages is demonstrated using test materials prepared from sulphide-containing rocks in a series of chemical and microbial weathering experiments. The test results indicate that: (1) metal leaching can effectively proceed even in a near-neutral environment; and (2) the occurrence of acid mine drainage can be delayed due to cathodic protection of an acid-generating sulphide such as pyrite from oxidative dissolution. While microbial mediation may enhance the weathering of sulphides with a high electrode potential, the competing galvanic processes diminish the dominating role of the microbes in effecting the oxidation of sulphides with a low electrode potential when the sulphides occur in a mixed assemblage. In-situ potential measurements on sulphide surfaces with micro-electrodes demonstrated the occurrence of a significant potential difference between a contacting sulphide pair sufficient to sustain galvanic interaction for the duration of the experiments. It is also shown that galvanic sulphide oxidation and hence metal leaching can occur even under an oxygenated water cover. Therefore, subaqueous disposal may not be the best management option for all reactive mine wastes, especially those containing metals or trace elements that remain mobile under near-neutral pH conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".