Small-scale electricity generation using cow manure microbial fuel cells
Bibliographic record
Abstract
Humanity is in the midst of a fossil fuel dependency that may leave it unable to adequately respond to future energy needs. As the number of inhabitants on earth increases, it is vital to find methods of energy generation coupled with organic waste utilization that are sustainable. This thesis is an investigation of manure microbial fuel cell (MFC) technology. Manure MFCs offer an additional opportunity to gain value with little reduction in the manure's soil building value, while concurrently reducing the manure's pollution potential. A variety of factors affecting power generation were investigated including ionic strength, temperature, suitable electrodes, and substrate consistency, all of which impact internal resistance. A scaleable MFC model was constructed based on knowledge gleaned from the pilot stage and was able to generated power densities as high as 5.46 mW/m2 with peak power of 85 W. MFCs can be utilised to trickle charge ultracapacitors for battery operated applications.
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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) | 0.000 | 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) | 0.001 | 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".