Enhancing Biosludge Dewaterability with Hemoglobin from Waste Blood as a Bioflocculant
Bibliographic record
Abstract
Synthetic polymers are widely used in the treatment of biosludge (waste activated sludge) to enhance its dewaterability. This paper discusses the results of a systematic study using hemoglobin (Hb) from animal blood and methylated hemoglobin (MeHb), a derivative in which a methyl group replaces the hydrogen carboxyl groups, to replace synthetic polymers to improve the dewatering efficiency of biosludge. With regular hemoglobin, no improvement in biosludge dewatering was found. With 10% of methylated hemoglobin per total solids content, however, the dry solids content of biosludge increased from 10.2 (±0.3) wt% to 15.0 (±1.0) wt%. Zeta potential measurements showed a decrease in the negative surface charge of the particles in biosludge from -34.3 (±3.2) mV to -19.0 (±2.1) mV after the treatment with methylated hemoglobin. This, along with an unchanged particle size distribution after conditioning, suggests that charge neutralization is likely the main cause of particle flocculation. With charges neutralized, the extracellular polymeric substances (EPS) around the biosludge flocs become loose, releasing the trapped water, thus increasing dewaterability.
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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) | 0.000 | 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".