Activation energy measurements to determine metabolic bottlenecks of a bioelectrochemical system studied using microfluidics and the Arrhenius equation
Bibliographic record
Abstract
To target development of bioelectrochemical systems, we developed an advanced microfluidic method to identify reaction bottlenecks in the metabolic activity of a pure-culture Geobacter sulfurreducens electroactive biofilm (EAB). The microfluidic system was devised to include perpendicular flow orientation for improved boundary layer uniformity and was combined with an embedded 3-electrode system to accurately apply a constant potential during the entire experimental duration. A 3-sensor temperature control system provided the basis of accurate temperature pulsing, which modified the EAB metabolic activity over short time intervals relative to the bacterial doubling rate. The system, together with the unique ability to control hydrodynamic, electrochemical, and thermal conditions, was used as the basis for an Arrhenius approach to obtain activation energy barrier values at different growth times, acetate concentrations, and flow rates. The results indicated that bottlenecks in the overall metabolic activity after 1 month of growth time were related to electron transfer through extracellular cytochrome c. After the EAB further matured to 4 months old, the bottleneck appeared to switch to enzyme-driven acetate oxidation. Based on this hypothesis, we observed after 4-months, that strong increases in effective enzyme concentration were primarily obtained by increasing flow rate, and secondarily by increasing acetate concentration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".