Biological oxidation of ferrous ions under acidic conditions using rotating biological contactor
Bibliographic record
Abstract
Oxidation of ferrous (Fe2+) ion to ferric (Fe3+) ion under acidic conditions can be achieved by iron oxidizing bacteria. In this research study, oxidation of Fe2+ ions by iron oxidizing bacteria was studied using a bench-scale rotating biological contactor (RBC). Experiments were conducted to investigate the effects of parameters such as hydraulic loading rate (HLR), temperature and Fe2+ concentration at pH 2.0 on Fe2+ oxidation. Oxidation of Fe2+ was observed to decrease with temperature (in the range of 5 to 23 °C). The Fe2+ oxidation rates of 35.3 g Fe2+/(m2·d) and 52.6 g Fe2+/(m2·d) were observed at 5 °C and 21 °C, respectively, at HLR of 0.014 m3/(m2·d). The Fe2+ oxidation rates increased with increase in HLR from 0.014 m3/(m2·d) to 0.055 m3/(m2·d) for a Fe2+ concentration of approximately 3200 mg/L in the RBC feed. The maximum Fe2+ oxidation rate observed in this study was 165 g Fe2+/(m2·d). Iron solids were deposited on the RBC disks and were identified as jarosite. The RBC was able to achieve 50% Fe2+ oxidation efficiency after 24 h of a process upset. Key words: rotating biological contactor, ferrous, ferric, oxidation, acidic mine drainage, hydraulic retention time, hydraulic loading rate.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".