Hydrogen production and microbial kinetics of Clostridium termitidis in mono-culture and co-culture with Clostridium beijerinckii on cellulose
Bibliographic record
Abstract
Cellulose utilization by hydrogen producers remains an issue due to the low hydrogen yields reported and the pretreatment of cellulose prior to fermentation requires complex and expensive steps. Clostridium termitidis is able to breakdown cellulose into glucose and produce hydrogen. On the other hand, Clostridium beijerinckii is not able to degrade cellulose but is adept at hydrogen production from glucose; therefore, it was chosen to potentially enhance hydrogen production when co-cultured with C. termitidis on cellulose. In this study, batch fermentation tests were conducted to investigate the direct hydrogen production enhancement of mesophilic cellulolytic bacteria C. termitidis co-cultured with mesophilic hydrogen producer C. beijerinckii on cellulose at 2 g l −1 compared to C. termitidis mono-culture. Microbial kinetics parameters were determined by modeling in MATLAB. The achieved highest hydrogen yield was 1.92 mol hydrogen mol −1 hexose equivalent added in the co-culture compared to 1.45 mol hydrogen mol −1 hexose equivalent added in the mono-culture. The maximum hydrogen production rate of 26 ml d −1 was achieved in the co-culture. Co-culture exhibited an overall 32 % enhancement of hydrogen yield based on hexose equivalent added and 15 % more substrate utilization. The main metabolites were acetate, ethanol, lactate, and formate in the mono-culture, with also butyrate in the co-culture. Additionally, the hydrogen yield of C. beijerinckii only in glucose was 2.54 mol hydrogen mol −1 hexose equivalent. This study has proved the viability of co-culture of C. termitidis with C. beijerinckii for hydrogen production directly from a complex substrate like cellulose under mesophilic conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".