Enrichment of Secondary Wastewater Sludge for Production of Hydrogen from Crude Glycerol and Comparative Evaluation of Mono-, Co- and Mixed-Culture Systems
Bibliographic record
Abstract
Anaerobic digestion using mixed-culture with broader choice of pretreatments for hydrogen (H₂) production was investigated. Pretreatment of wastewater sludge by five methods, such as heat, acid, base, microwave and chloroform was conducted using crude glycerol (CG) as substrate. Results for heat treatment (100 °C for 15 min) showed the highest H₂ production across the pretreatment methods with 15.18 ± 0.26 mmol/L of medium at 30 °C in absence of complex media and nutrient solution. The heat-pretreated inoculum eliminated H₂ consuming bacteria and produced twice as much as H₂ as compared to other pretreatment methods. The fermentation conditions, such as CG concentration (1.23 to 24 g/L), percentage of inoculum size (InS) (1.23% to 24% v/v) along with initial pH (2.98 to 8.02) was tested using central composite design (CCD) with H₂ production as response parameter. The maximum H₂ production of 29.43 ± 0.71 mmol/L obtained at optimum conditions of 20 g/L CG, 20% InS and pH 7. Symbiotic correlation of pH over CG and InS had a significant (p-value: 0.0011) contribution to H₂ production. The mixed-culture possessed better natural acclimatization activity for degrading CG, at substrate inhibition concentration and provided efficient inoculum conditions in comparison to mono- and co-culture systems. The heat pretreatment step used across mixed-culture system is simple, cheap and industrially applicable in comparison to mono-/co-culture systems for H₂ production.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".