Dynamics of bacterial streamers induced clogging in microfluidic devices
Bibliographic record
Abstract
Using a microfabricated porous media mimic platform, we investigated the clogging dynamics of bacterial biomass that accumulated in the device due to the formation of bacterial streamers. Particularly, we found the existence of a distinct clogging front which advanced via pronounced 'stick-slip' of the viscoelastic bacterial biomass over the solid surface of the micro pillar. Thus, the streamer, the solid surface, and the background fluidic media defined a clear three-phase front influencing these advancing dynamics. Interestingly, we also found that once the clogging became substantial, contrary to a static homogenous saturation state, the clogged mimic exhibited an instability phenomena marked by localized streamer breakage and failure leading to extended water channels throughout the mimic. These findings have implications for design and fabrication of biomedical devices and membrane-type systems such as porous balloon catheters, porous stents and filtration membranes prone to bacteria induced clogging as well as understanding bacterial growth and proliferation in natural porous media such as soil and rocks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".