Aqueous solubility of Cr(VI) compounds in ferrochrome bag filter dust and the implications thereof
Bibliographic record
Abstract
The production of ferrochrome (FeCr) is a reducing process. However, it is impossible to completely exclude oxygen from all of the high-temperature production process steps, which may lead to unintentional formation of small amounts of Cr(VI). The majority of Cr(VI) is associated with particles found in the off-gas of the high-temperature processes, which are cleaned by means of venturi scrubbers or bag filter dust (BFD) systems. BFD contains the highest concentration of Cr(VI) of all FeCr wastes. In this study, the solubility of Cr(VI) present in BFD was determined by evaluating four different BFD samples. The results indicate that the currently applied Cr(VI) treatment strategies of the FeCr producer (with process water pH ≤ 9) only effectively extract and treat the water-soluble Cr(VI) compounds, which merely represented approximately 31% of the total Cr(VI) present in the BFD samples evaluated. Extended extraction time, within the afore-mentioned pH range, proved futile in extracting sparingly-soluble and water-insoluble Cr(VI) species, which represented approximately 34% and 35% of the total Cr(VI), respectively. Due to the deficiencies of the current treatment strategies, it is highly likely that sparingly water-soluble Cr(VI) compounds will leach from waste storage facilities (e.g. slimes dams) over time. Therefore, it is critical that improved Cr(VI) treatment strategies be formulated, which should be an important future perspective for FeCr producers and researchers alike.Keywords: hexavalent chromium, Cr(VI), ferrochromium, ferrochrome, bag filter dust, smelter waste
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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 | 0.000 | 0.000 |
| 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".