Impact of bacterial streamers on biofouling of microfluidic filtration systems
Bibliographic record
Abstract
We investigate the effect of biofouling in a microfluidic filtration system. The microfluidic platform consists of cylindrical microposts with a pore-spacing of 2 μm, which act as the filtration section of the device. One of our key findings is that there exists a critical pressure difference above which pronounced streamer formation is observed, which eventually leads to rapid clogging of the device with an accompanying exponential decrease in permeate flow. Moreover, when streamers do form, de-clogging of pores also occurs intermittently, which leads to small time scale fluctuations [O(101 s)] superimposed upon the large time scale [O(102 min)] clogging of the system. These de-clogging phenomena lead to a sharp increase in water permeation through the microfluidic filtration device but rates the water quality as biomass debris is transported in the permeate. Streamer-based clogging shares similarities with various fouling mechanisms typically associated with membranes. Finally, we also show that the pH of the feed strongly affects biofouling of the microfluidic filtration system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".