A defined co‐culture of <i>Geobacter sulfurreducens</i> and <i>Escherichia coli</i> in a membrane‐less microbial fuel cell
Bibliographic record
Abstract
Wastewater-fed microbial fuel cells (MFCs) are a promising technology to treat low-organic carbon wastewater and recover part of the chemical energy in wastewater as electrical power. However, the interactions between electrochemically active and fermentative microorganisms cannot be easily studied in wastewater-fed MFCs because of their complex microbial communities. Defined co-culture MFCs provide a detailed understanding of such interactions. In this study, we characterize the extracellular metabolites in laboratory-scale membrane-less MFCs inoculated with Geobacter sulfurreducens and Escherichia coli co-culture and compare them with pure culture MFCs. G. sulfurreducens MFCs are sparged to maintain anaerobic conditions, while co-culture MFCs rely on E. coli for oxygen removal. G. sulfurreducens MFCs have a power output of 128 mW m(-2) , compared to 63 mW m(-2) from the co-culture MFCs. Analysis of metabolites shows that succinate production in co-culture MFCs decreases current production by G. sulfurreducens and that the removal of succinate is responsible for the increased current density in the late co-culture MFCs. Interestingly, pH adjustment is not required for co-culture MFCs but a base addition is necessary for E. coli MFCs and cultures in vials. Our results show that defined co-culture MFCs provide clear insights into metabolic interactions among bacteria while maintaining a low operational complexity.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".