Real-Time Performance Optimization and Diagnostics during Long-Term Operation of a Solid Anolyte Microbial Fuel Cell Biobattery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study describes a novel approach for real-time energy harvesting and performance diagnostics of a solid anolyte microbial fuel cell (SA-MFC) representing a prototype smart biobattery. The biobattery power output was maximized in real time by combining intermittent power generation with a Perturbation-and-Observation algorithm for maximum power point tracking. The proposed approach was validated by operating the biobattery under a broad range of environmental conditions affecting power production, such as temperature (4–25 °C), NaCl concentration (up to 2 g L−1), and carbon source concentration. Real-time biobattery performance diagnostics was achieved by estimating key internal parameters (resistance, capacitance, open circuit voltage) using an equivalent electrical circuit model. The real time optimization approach ensured maximum power production during 388 days of biobattery operation under varying environmental conditions, thus confirming the feasibility of biobattery application for powering small electronic devices in field applications.
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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) | 0.002 | 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 it