Bacteria Energy Recovery System Using Natural Soil Bacteria in Microbial Fuel Cells
Bibliographic record
Abstract
This paper describes a two-cycle bacteria energy recovery system (BERS) to power two embedded sensors: an ultra-low portable pH sensor and a sound sensor. The designed unit can handle up to seven microbial fuel cells (MFCs) to charge a super-capacitor. This allows the BERS to provide a constant 0.14 mW without further electrical components for signal conditioning. The two cycles were driven with a 100 kΩ load and a 10 Hz frequency. The BERS is also self-powered with an integrated start-up unit to be self-activated when the MFCs charge the energy-storing unit after three days. The BERS powered pH sensor has an error below 5% at 25 ∘C and is able to work continuously while being activated for 4 h. The performances of the pH and sound sensors were determined based on a compromise between accuracy and power consumption.
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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 | 0.000 | 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 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".