Composite Mesh Electrodes with Immobilized Bacteria for Bio-Batteries
Bibliographic record
Abstract
An anode was constructed using a novel technique and subsequently tested in a bio-battery. The anode comprised of a composite electrode coated with immobilized bacteria. The immobilized bacteria used in this study were Escherichia coli K-12. The composite electrode contained three layers: a 304 L stainless steel mesh base, an electro-polymerized layer of pyrrole, and an electro-polymerized layer of methylene blue. The bacteria were immobilized utilizing a technique incorporating a carbon nanoparticle and TeflonTM emulsion. The composite electrode combined with immobilized bacteria was examined whilst incorporated into the anodic chamber of a bio-battery. Different tests were conducted, including Electrochemical Impedance Spectroscopy. Results from these tests were compared with data obtained from alternate configurations and values from the open literature. The maximum power density generated by the composite electrode with immobilized bacteria whilst incorporated into the anodic chamber of a bio-battery was 378 mW/m2. Results demonstrate this composite anode configuration with immobilized bacteria produced approximately 69% more power density and 53% more current density than alternate electrode configurations with bacteria suspended in solution. Also, it was found that a significant portion of the bio-battery’s resistance to charge transfer occurred at the surface of the anode and this resistance was lowered by 51% through bacteria immobilization.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.001 |
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".