A High‐Performance Membraneless Microfluidic Microbial Fuel Cell for Stable, Long‐Term Benchtop Operation Under Strong Flow
Bibliographic record
Abstract
Abstract Strong control over experimental conditions in microfluidic channels provides a unique opportunity to study and optimize membraneless microbial fuel cells (MFCs), particularly with respect to the role of flow. However, improved performance and transferability of results to the wider MFC community require improvements to device stability under all applied operational conditions. To address these challenges, we present an easy‐to‐fabricate membraneless MFC that combines i) O2 protection via a gas diffusion barrier, ii) integrated graphite electrodes, and iii) optimized electrode placement to avoid cross‐contamination under all applied flow rates. Attention to all of these design features in the same platform resulted in the operation of a MFC with a pure‐culture anaerobic Geobacter sulfurreducens biofilm for half a year, that is, six times longer than previously reported, without the use of an oxygen scavenger. As a result of higher device stability under high flow rates, power densities were four times higher than reported previously for microfluidic MFCs with the same biofilm.
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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 | 0.001 | 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".