Aqueous Geochemistry and Mineralogy of Tungsten with Emphasis on Mine Wastes
Bibliographic record
Abstract
Abstract Tungsten is a valuable industrial metal with limited effective substitutes for its many industrial uses. Tungsten is classified as a critical mineral by many countries, including Canada and the United States. As such, tungsten mining is expected to increase in the future, generating waste with potential as point sources of metal leaching to the environment. Concerns about the toxicity of tungsten have recently emerged, but the element is not regulated in mine waste. The geochemical behavior of tungsten is understudied, hampering the ability to predict tungsten leaching from past, present, and future mining operations. The low-temperature aqueous mobility of tungsten is pH dependent, with adsorption as a primary factor limiting its dissolved concentrations in the environment. Tungsten, which forms strictly anionic species, adsorbs to mineral surfaces at low pH, and is most mobile in alkaline waters. The speciation of tungsten has been shown to affect its adsorption propensity, with WO42- more strongly adsorbed than polymeric and thiolated species. Aqueous tungsten concentrations generally decrease with decreasing pH in surface waters, groundwaters, geothermal waters, and mine tailings. Although progress has been made, the mechanisms of scheelite and wolframite dissolution are still poorly understood. Mine waste generated from processing tungsten-rich ores contains elevated tungsten concentrations; the weathering behavior of scheelite and wolframite need more research to mitigate the potential for tungsten leaching during the long-term storage of mine waste. Identifying mineralogical changes to scheelite and wolframite that may occur during ore processing and weathering of mine waste would be beneficial for understanding the leaching behavior of these minerals. Based on current knowledge, it is likely that tungsten is mobilized as both dissolved anions and adsorbed to colloidal particles. Improved understanding of the environmental geochemistry of tungsten will help ensure its sustainable supply in the future and permit more effective remediation at abandoned and existing mines.
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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 | 0.000 | 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".