Modulation of biofilm growth by shear and fluctuations in turbulent environments
Bibliographic record
Abstract
This work investigates the role of shear and turbulent fluctuations on multi-species biofilm growth. The study is mostly motivated by understanding biofouling on microplastics (MPs) in oceanic environments. By increasing particle stickiness, biofilms promote MP aggregation and sinking; therefore, a thorough understanding of this multi-scale process is crucial to improve predictions of the MPs fate. We conducted a series of laboratory experiments using an oscillating-grid system to promote biofilm growth on small plastic surfaces under homogeneous isotropic turbulence with grid Reynolds numbers between 305 and 2220. Two configurations were analyzed: one where plastic samples move along with the grid (shear-dominated) and another one where the samples are kept fixed downstream the grid, thus experiencing turbulence but no mean flow (shear-free). Biofilm formed in all cases in a time scale of days, then the biomass formed on the plastic pieces was carefully measured and analyzed as a function of the turbulence level. The shear-free results were further interpreted using a parsimonious physical model, coupling the nutrient uptake rate within the biofilm (Monod kinetics) with the turbulent diffusion of the surrounding bulk liquid. Results show that: (i) under shear-dominated conditions, the biofilm mass initially grows with turbulence intensity before decaying, presumably due to shear-induced erosion; (ii) in the shear-free experiments, the mass increases monotonically following an enhanced availability of nutrients, and then saturates due to uptake-limited kinetics. This latter behavior is well reproduced by the physical model. Furthermore, a subset of plastic pieces were analyzed with a scanning electron microscope, revealing that turbulence also affects the microscopic configuration of biofilm clusters, increasing their compactness as the amplitude of turbulent fluctuations increases. These results contribute not only to our fundamental understanding of biofilms under flow, but can also inform global models of MP transport in marine environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".