Oxidation of Ferrous Sulfate Hydrolyzed Slurry—Kinetic Aspects and Impact on As(V) Removal
Bibliographic record
Abstract
In this paper the air sparging-oxidation kinetics of hydrolyzed iron(II) sulfate slurries in connection to acidic effluent treatment by neutralization for the removal of contaminants like arsenic(V) were investigated. It was shown in the absence of As(V) and forced air sparging that Fe(II) sulfate of initial concentration 75 mmol/L hydrolyzed completely between pH 7.5 and 8.5 at 22 °C. Subsequent oxidation by forced air sparging of the ferrous hydroxide slurry was found to proceed via a series of transformations starting from ferrous hydroxide to green rust, to lepidocrocite or magnetite depending on the pH and rate of oxidation, and finally to goethite. The oxidation kinetics at pH 8 or higher were governed by oxygen mass transfer while at pH 6 they were chemically controlled with autocatalytic behavior arising from the effect of in situ formed ferric oxyhydroxide. In the presence of As(V), both Fe(II) and As(V) precipitated from solution starting at pH 4 with the latter ultimately dropping below 1 mg/L past pH 6.5 via the apparent formation of ferrous arsenate compound. Subsequent oxidation by air sparging of the Fe(II)–As(V) slurry at constant pH 8 led to destabilization of the arsenate-carrying phase resulting in partial release of As(V). The bulk control of As(V) in the latter case appears to switch from ferrous arsenate to arsenate adsorption on in situ formed iron(III) oxyhydroxide.
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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 | 0.000 | 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".