Synergy of Electricity Generation and Waste Disposal in SolidState Microbial Fuel Cell (MFC) of Cow Manure Composting
Bibliographic record
Abstract
A small-scale, composting, microbial fuel cell (MFC) system was constructed that used cow manure as the reduced carbon energy source. The system was a single-chamber, air-cathode MFC with a reactor, resistance box and data processing unit. Factors such as moisture content, concentration of phosphate buffer solution (PBS), catalyst addition and electrode area were investigated. Moisture contents of 80%, 70% and 60% resulted in maximum power densities of 349±39, 36±9 and 12±2 mW m-2, respectively. A moisture content of greater than 80% is suitable for generation of current in the composting MFC. Addition of 0.1 mg Pt cm-2 catalyst resulted in 10-fold greater maximum power density with an output voltage twice as great as that generated in the absence of the catalyst. A concentration of 100 mM PBS resulted in maximum power density and output voltage. The power per unit area of electrode was inversely proportional to surface area of the electrode. Quantification of carbon, hydrogen and nitrogen (CHN) content indicated enhanced degradation or organic compounds in addition to production of the electric current. The diversity of the microbial community, as determined by denaturing gradient gel electrophoresis (DGGE) was directly proportional to content of water, but inversely proportional to concentration of PBS. The results of this study demonstrated that the composting MFC can be used to treat wastes while generating electric current.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".