Experimental Study of Ferrous Iron Biooxidation by <i>Leptospirillum Ferriphilum </i>in Different Biofilm Reactors
Bibliographic record
Abstract
The process of biological oxidation of ferrous iron by the microorganism Leptospirillum ferriphilum was studied in different types of biofilm reactors. A total of 12 bioreactor types with both fixed and mobile support were used. The biofilm supports used had different shapes and were made of: polyethylene, nylon, polystyrene, polyvinylidene difluoride, polyester, ceramics, carbon and PVC. The pH of the microbial medium was maintained around 1.0, the temperature was 40°C while the influent ferrous iron concentration was 20 g/L. Iron oxidation rates of up to 4.5 g/L/h were obtained. The most efficient were the bioreactors with polyethylene and nylon woven fabric support. However, they oxidized ferrous iron at high rate for relatively short time periods - 40 to 60 days. While the bioreactor with a fixed bed of Raschig rings support had lower iron oxidation rate, their long-term stability was much higher. Of all the biofilm support materials tested, it was found that only polyvinylidene difluoride did not allow the formation of biofilm. Since no significant amounts of jarosite were formed at pH of 1.0 and below, the biofilm formed was very weak mechanically. For that reason the moving support, such as inverse fluidized bed, was not very appropriate because of the high shear stress.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".