Previously unknown mineral-nanomineral relationships with important environmental consequences: The case of chromium release from dissolving silicate minerals
Bibliographic record
Abstract
Risk assessments that take into account the formation of environmentally dangerous hexavalent chromium in Cr-containing mine tailings, and associated soils and sediments, require an understanding of the occurrence and speciation of Cr in silicate minerals and glasses. Silicates are more soluble and generally more susceptible to weathering than the refractory mineral chromite, the principal ore mineral of Cr. Studies at the nanoscale using a combination of advanced sample preparation via microtoming and focused ion beam techniques, in combination with state-of-the art analytical transmission electron microscopy and electron diffraction, reveal the occurrence of chromite nanoparticles held within clinochlore and lizardite grains in chromitite ore (an igneous cumulate consisting primarily of chromite) from the Black Thor Chromium deposit in Northern Ontario, Canada, and the Mistake Mine, Fresno County, California, U.S.A., respectively. Nanoscale examinations of altered chromitite ore samples from the Black Thor deposit after dissolution experiments in sulfuric acid-bearing solutions of pH 2.5 show that clinochlore alters to amorphous silica depleted in chromite nanoparticles. This observation suggests the release of chromite nanoparticles rather than Cr 3+ aqueous species during the weathering of chromite-bearing silicate minerals. This will in turn have an impact on the environmental behavior of Cr 3+ and its potential oxidation to Cr 6+ . The formation of Craq6+$\begin{array}{} \rm Cr_{aq}^{6+} \end{array} $ species in this case will require either the initial dissolution of the nanoparticles or the oxidation of Cr 3+ species on the surface of the nanoparticles, either process being a rate limiting step in the formation of Craq6+$\begin{array}{} \rm Cr_{aq}^{6+} \end{array} $ species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".