Role of mixing on microwave-enhanced advanced oxidation process in treating sewage sludge
Bibliographic record
Abstract
The microwave enhanced advanced oxidation process (MW/H2O2-AOP) was used for the release of nutrients and the disintegration of suspended solids from both anaerobic sludge and aerobic sludge. The purpose of this study was to determine the effects of mixing on the performance of the process, in terms of soluble ammonia, orthophosphate and soluble chemical oxygen demands. Experiments were conducted on sludge samples with various total solids concentrations (1.1-3.7%) and hydrogen peroxide dosage (1% per 1% of total solids) at 80 degrees C of microwave temperature and five minutes of heating time. The results indicated that mixing affected solids disintegration and nutrient solubilization of sewage sludge, regardless of the sludge used, anaerobic or aerobic. However, the effects of mixing on the MW/H2O2-AOP were dependent on the total solids concentration of the sludge. A paired t-test was performed on data for aerobic sludge: at 2.9% of total solids (TS), the difference for solubilization of nutrients and solids disintegration was statistically significant at a 95% confidence level between mixing and non-mixing samples. At a lower TS of 1.7% only soluble chemical oxygen demand showed significant difference between mixing and non-mixing. The results suggest that, for sludge with higher solids content, the MW/H2O2-AOP can be more effective if a mixing device is implemented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".