Biohydrogen and Bioethanol Production from Biodiesel-Based Glycerol by Enterobacter aerogenes in a Continuous Stir Tank Reactor
Bibliographic record
Abstract
Crude glycerol from the biodiesel manufacturing process is being produced in increasing quantities due to the expanding number of biodiesel plants. It has been previously shown that, in batch mode, semi-anaerobic fermentation of crude glycerol by Enterobacter aerogenes can produce biohydrogen and bioethanol simultaneously. The present study demonstrated the possible scaling-up of this process from small batches performed in small bottles to a 3.6-L continuous stir tank reactor (CSTR). Fresh feed rate, liquid recycling, pH, mixing speed, glycerol concentration, and waste recycling were optimized for biohydrogen and bioethanol production. Results confirmed that E. aerogenes uses small amounts of oxygen under semi-anaerobic conditions for growth before using oxygen from decomposable salts, mainly NH4NO3, under anaerobic condition to produce hydrogen and ethanol. The optimal conditions were determined to be 500 rpm, pH 6.4, 18.5 g/L crude glycerol (15 g/L glycerol) and 33% liquid recycling for a fresh feed rate of 0.44 mL/min. Using these optimized conditions, the process ran at a lower media cost than previous studies, was stable after 7 days without further inoculation and resulted in yields of 0.86 mol H2/mol glycerol and 0.75 mol ethanol/mole glycerol.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".