Halobacterium salinarum NRC-1 Sustains Voltage Production in a Dual-Chambered Closed Microbial Fuel Cell
Bibliographic record
Abstract
Sustained bioenergy production from organisms that thrive in high salinity, low oxygen, and low nutrition levels is useful in monitoring hypersaline polluted environments. Microbial fuel cell (MFC) studies utilizing single species halophiles under salt concentrations higher than 1 M and as a closed microbial system are limited. The current study aimed to establish baseline voltage, current, and power density from a dual-chambered MFC utilizing the halophile Halobacterium salinarum NRC-1. MFC performance was determined with two different electrode sizes (5 cm2 and 10 cm2), under oscillating and nonoscillating conditions, as well as in a stacked series. A closed dual-chamber MFC system of 100 mL capacity was devised with Halobacterium media (4.3 M salt concentration) as both anolyte and catholyte, with H. salinarum NRC-1 being the anodic organism. The MFC measured electrical output over 7, 14, 28, and 42 days. MFC output increased with 5 cm2 sized electrodes under nonoscillating ( p < 0.0001 ) relative to oscillating conditions. However, under oscillating conditions, doubling the electrode size increased MFC output significantly ( p = 0.01 ). The stacked series MFC, with an electrode size of 10 cm2, produced the highest power density (1.2672 mW/m2) over 14 days under oscillation. Our results highlight the potentiality of H. salinarum as a viable anodic organism to produce sustained voltage in a closed-MFC system.
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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) | 0.000 | 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 | 0.000 | 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".