Flow‐Based Deacidification of <i>Geobacter sulfurreducens</i> Biofilms Depends on Nutrient Conditions: a Microfluidic Bioelectrochemical Study
Bibliographic record
Abstract
Abstract Biofilms from Geobacter sulfurreducens are promising materials for new bioelectrochemical systems. To improve the performance of such systems, limitations related to biofilm acidification should be addressed. This work examines a long‐held assumption that liquid flow can deacidify biofilm pH by enhancing molecular mass transport in the biofilm subdomain. A microfluidic electrochemical system was used to measure changes to biofilm pH in situ while accurately modulating hydrodynamic conditions under turnover, nutrient‐limited and starvation conditions. We discovered that increased flow rates could indeed mitigate biofilm acidification, but not under turnover concentrations, which are the predominant conditions used in research studies. This effect is demonstrated with the observation that relative increases to bio‐current under increased flow rates were stronger for experiments conducted under nutrient‐limited concentrations compared to turnover concentrations. This can open the way for a solution to poor performance of some bioelectrochemical systems at low concentrations.
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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) | 0.000 | 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 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".