Microaerobic dark fermentative hydrogen production by the photosynthetic bacterium,<i>Rhodobacter capsulatus</i>JP91
Bibliographic record
Abstract
The photosynthetic bacterium Rhodobacter capsulatus produces hydrogen under nitrogen-limited, anaerobic, photosynthetic conditions. The present study examined whether R. capsulatus can produce hydrogen under microaerobic conditions in the dark with limiting amounts of O2 and fixed nitrogen. The relationship between hydrogen production, different O2 concentrations and carbon sources as well as two different N sources, glutamate and ammonium, were studied in batch culture using a Hup strain of R. capsulatus. The effect of different O2 concentrations, ranging from 0.5 to 20%, on hydrogen production was examined in dark batch cultures of R. capsulatus grown on RCV medium. Different carbon sources, e.g. glucose, succinate, lactate, acetate and malate, were used at various concentrations (20–40 mM). Similarly, different concentrations of glutamate and ammonium (2–9 mM) were examined for optimum microaerobic dark hydrogen production. Maximum hydrogen production was observed at an O2 concentration of 4–8%. There was a highly positive correlation between O2 and growth (r2 = 0.67), whereas O2 concentration and hydrogen productivity were negatively correlated (r2 = −0.3). Succinate (25 mM) together with glutamate (3.5 mM) gave the highest specific hydrogen productivity [5.61 μmol hydrogen/(mg cell dry weight/ml)]. The maximum average hydrogen yield was 0.6 mol hydrogen/mol malate followed by 0.41 mol hydrogen/mol lactate, 0.36 mol hydrogen/mol succinate, whereas minimum amounts of hydrogen were produced from glucose and acetate (0.16 mol hydrogen/mol and 0.07 mol hydrogen/mol, respectively). The implications for developing a system capable of improved hydrogen production are discussed.
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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) | 0.000 | 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".