Effect of Hydrothermal Pretreatment on the Acidification of Thickened Waste Activated Sludge and Source Separated Organics
Bibliographic record
Abstract
The objective of this study was to investigate the impact of the hydrothermal pre-treatment (HTP) on solubilization and acidification of thickened waste activated sludge (TWAS) and source separated organics (SSO). The temperatures, retention times, and pressures used in this study ranges were 150-240°C, 5-30 min, and 69-488 psi, respectively. Mesophilic batch acidification tests were conducted for all pretreated and non-pretreated samples. For the TWAS, the highest overall COD solubilization due to HTP and acidification of 64% was observed at “200°C-10 min” compared to 30% for raw TWAS. The highest VFAs yield of 2856 mg VFAs/g VSS added was observed at “190°C-10 min” compared to 1251 for raw TWAS. For the SSO, the highest overall COD solubilization of 63% was observed at “210°C-20 min” compared to 17% for raw SSO. The highest VFAs yield of 1536 mg VFAs/g VSS added was observed at “210°C-20 min” compared to 768 for raw SSO.
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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) | 0.001 | 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".