Initial examination of microwave pretreatment on primary, secondary and mixed sludges before and after anaerobic digestion
Bibliographic record
Abstract
The effects of microwave pretreatment on disintegration and mesophilic digestion of waste activated sludge (WAS), primary sludge (PS), combined (PS + WAS) sequencing batch reactor (SBR) sludge and anaerobically digested biocake were investigated by both household and bench scale industrial types microwaves at temperatures below and above boiling point. Pretreatment variables, temperature, intensity (cooking rate) and sludge concentration had statistically significant effects on solubilization. The microwave pretreatment also increased the bioavailability of sludge components under batch anaerobic digestion and enhanced the dewaterability of pretreated sludges after digestion. However, the level of improvements in solubilization and biodegradation from different waste sludges were different. While the largest improvement in ultimate biodegradation was observed in WAS, microwave irradiation only affected the rate of biodegradation of pretreated PS samples. Similarly, relatively lower solubilization ratios achieved for combined - SBR sludge was attributed to high sludge age of extended aeration SBR unit. It is possible that initial sludge characteristics may influence final pretreatment outcomes so that general statements of performance cannot always be made.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".