Effects of Electrokinetic Phenomena on Bacterial Deposition Monitored by Quartz Crystal Microbalance with Dissipation Monitoring
Bibliographic record
Abstract
Bacterial deposition is the first step in the formation of microbial biofilms in environmental technology, and there is high interest in controlling such deposition. Earlier work indicated that direct current (DC) electric fields could influence bacterial deposition in percolation columns. Here, a time-resolved quartz crystal microbalance with dissipation monitoring (QCM-D) and microscopy-based cell counting were used to quantify DC field effects on the deposition of bacterial strains Pseudomonas putida KT2440 and Pseudomonas fluorescens LP6a at varying electrolyte concentrations and weak electric field strengths (0–2 V cm–1). DC-induced frequency shifts (Δf), dissipation energy (ΔD), and ratios thereof (Δf/ΔD) proved as good indicators of the rigidity of cell attachment. We interpreted QCM-D signals using a theoretical approach by calculating the attractive DLVO-force and the shear and drag forces acting on a bacterium near collector surfaces in a DC electric field. We found that changes in DC-induced deposition of bacteria depended on the relative strengths of electrophoretic drag and electro-osmotic shear forces. This could enable the prediction and electrokinetic control of microbial deposition on surfaces in natural and manmade ecosystems.
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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 | 0.001 |
| 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".