Vacuum-enhanced anaerobic fermentation: Achieving process intensification, thickening and improved hydrolysis and VFA yields in a single treatment step
Bibliographic record
Abstract
(IC), under mild vacuum pressure (110 mbar), compared to a control (conventional fermenter), and evaluated the impact of the vacuum on the activities of various microbial groups. Both fermenters (test and control) were operated with mixed (50% v/v) municipal sludge at solids concentrations of 2-2.5%, pH of 7.8-8.1, 40-45 °C, a theoretical solids retention time (SRT) of 3 days with different hydraulic retention times (HRT). The intensification factor (IF) of the IC, defined as SRT/HRT, was controlled at 1.3 and 2.0. Simultaneous thickening and fermentation intensification were achieved. Compared with the control, the IC, despite the shorter HRTs, achieved 29.5 to 90.2% increase in the VFA yield (79 to 116 mg ΔVFA/ g VSS vs 61 mg ΔVFA/ g VSS), and 16.2% to 56.4% increase (280 to 377 mg ΔsCOD/ g VSS vs 241 mg ΔsCOD/ g VSS), in the hydrolysis yield. Fermentate from the IC exhibited comparable specific denitrification rates to acetate. Further, the solids-free condensate contained low nutrient concentrations, and thus was far superior to a typical centrates from dewatering as a carbon source. No adverse effects of vacuum on the activity of fermentative bacteria and methanogens were observed. This study demonstrated that the IC can be deployed as an intensification technology for both fermentation and anaerobic digestion of biosolids with the additional significant advantage, i.e. elimination of sidestream ammonia treatment requirements.
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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".