Comparison of Various Techniques to Characterize a Single Chamber Microbial Fuel Cell Loaded with Sulfate Reducing Biocatalysts
Bibliographic record
Abstract
A single-chamber microbial fuel cell (SCMFC) with a carbon supported Pt-cathode for the oxygen reduction reaction (ORR), and loaded with a sulfate reducing bacterial consortium as biocatalyst in the anodic chamber was characterized by polarization by variable resistance (VR) and linear sweep voltammetry (LSV) methods. From VR a whole cell configuration maximum volumetric power of 92.5 mW m-3 was attained at a current density of 459 A m-3 and voltage of 0.202 V. The LSV method of whole cell configuration gave a higher maximum power density of 197.5 mW m-3 at current density of 696 mA m-3 at the potential of 0.284V; this disagreement was ascribed to possible reduction of power and potential overshoot with the LSV. There was a fair agreement between internal resistance values of whole cell configuration determined by VR and electrochemical impedance spectroscopy (EIS): 2225 and 2307 Ω , respectively. Yet, internal resistance measured by LSV was 30% lower for the whole cell configuration. Both LSV and EIS show the advantage of reduced potential overshoot; yet, EIS provides more detailed information on equivalent circuit of the cell and resistance contributions of the electrodes, electrolyte and membrane. Further cyclic voltammetry tests gave midpoint potential of -0.215 V vs saturated calomel electrode, a value close to those reported for bacterial cytochromes involved in extracellular electron transfer processes. It is concluded that in spite of particular advantages of some techniques over others, the combination of electrochemical methods can be very valuable for shedding light and internal checking of the main characteristics of a microbial fuel cell.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".