Boosting microfluidic microbial fuel cells performance via investigating electron transfer mechanisms, metal-based electrodes, and magnetic field effect
Bibliographic record
Abstract
Abstract The presented paper fundamentally investigates the influence of different electron transfer mechanisms, various metal-based electrodes, and a static magnetic field on the overall performance of microfluidic microbial fuel cells (MFCs) for the first time to improve the generated bioelectricity. To do so, as the anode of microfluidic MFCs, zinc, aluminum, tin, copper, and nickel were thoroughly investigated. Two types of bacteria, Escherichia coli and Shewanella oneidensis MR-1 , were used as biocatalysts to compare the different electron transfer mechanisms. Interaction between the anode and microorganisms was assessed. Finally, the potential of applying a static magnetic field to maximize the generated power was evaluated. For zinc anode, the maximum open circuit potential, current density, and power density of 1.39 V, 138,181 mA m -2 and 35,294 mW m -2 were obtained, respectively. The produced current density is at least 445% better than the values obtained in previously published studies so far. The microfluidic MFCs were successfully used to power ultraviolet light-emitting diodes (UV-LEDs) for medical and clinical applications to elucidate their application as micro-sized power generators for implantable medical devices.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".