Effect of Hydraulic Retention Time on Anaerobic Baffled Reactor Operation: Enhanced Biohydrogen Production and Enrichment of Hydrogen-producing Acetogens
Bibliographic record
Abstract
Biohydrogen production by fermentation has become a promising technology developed in the world. In this study, diluted normal molasses wastewater is used as the raw material, and biohydrogen production efficiency and operation characteristics of an anaerobic baffled reactor (ABR) are studied. The effect of hydraulic retention time (HRT) on biohydrogen production efficiency and operating characteristics of ABR is extensively discussed. Experimental results showed that methanogen residuals were still observed in the last three compartments under HRT of 24 h and COD(Chemical oxygen demand) concentration of 8000 mg/L. Meanwhile, the first three compartments presented an ethanol fermentation type. The characteristics of butyric acid fermentation in Compartment IV were also enhanced. The average removal efficiency of COD was reduced to 15.4%. The average rates of biohydrogen production and specific biohydrogen production were 12.85 and 360.22 L/kg COD, respectively. The extension of HRT was beneficial to enrich hydrogen-producing acetogens and could increase the production rate of biohydrogen by a factor of 1.65. However, with the decrease in the bioactivity of acidogenic fermentation bacteria, the biohydrogen production efficiency of ABR was significantly reduced when HRT was longer than 30 h. The specific biogas production rate decreased from 191 to 92 L/(kg MLVSS·d). The specific biohydrogen production rate also decreased from 24.34 to 2.7 L/(kg MLVSS·d).
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".