Single Layer Deposition of Polystyrene Particles onto Planar Polydimethylsiloxane Substrates
Bibliographic record
Abstract
This work investigates the deposition of polystyrene particles onto cross-linked polydimethylsiloxane (PDMS) substrates by using an impinging jet flow cell for different concentrations of sodium chloride in solution. Particle tracking reveals that particles near the substrate can be immobilized to different degrees. An attempt is made to classify the mobility of the particles close to the surface by distinguishing between weakly immobilized and strongly immobilized particles where only the latter ones are considered as deposited. Subsequently, the measured initial deposition rates for different concentrations of sodium chloride in solution are compared to the commonly applied theory based on the convective diffusion equation in which different surface interaction potentials were considered. With currently available data on the surface properties of PDMS, the extended Derjaguin-Landau-Verwey-Overbeek (extended DLVO) theory gave a better description of the observed deposition rates as compared to the DLVO theory; however, in either case, the presence of significant surface charge heterogeneity had to be assumed in order to capture the observed trend of the deposition rates with respect to the electrolyte concentration. Careful analysis of the more weakly immobilized particles through particle displacement step analysis reveals that there is a buildup of a particle accumulation layer near the substrate in which particle motion parallel to the substrate is hindered by nonhydrodynamic effects. Possible reasons for the reduced particle motion in the accumulation layer are discussed. As a result, the presence of lateral surface interaction forces resulting from charge heterogeneity and surface roughness of the PDMS substrate is found to be the most plausible explanation for the hindered particle motion in the accumulation layer. This suggests that particles associated with the secondary minimum of the surface interaction potential may not always be freely mobile in any direction parallel to the substrate.
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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 | 0.000 |
| 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) | 0.001 | 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".