Role of polyelectrolyte charge density in tuning colloidal forces
Bibliographic record
Abstract
Abstract An atomic force microscope was used to study the effects of polymer charge density on surface interactions between similarly charged silica surfaces. Copolymers of acrylamide and acrylic acid of three different charge densities (f p = 15, 40, and 70%) were used. The dynamic light‐scattering technique was used to obtain the characteristic size of these polymers in solution. Flocculation tests were performed to complement force–distance measurement. At 20 mM KCl and pH ∼ 8.0, the low charge density copolymer (f p = 15%) caused a purely repulsive force profile between silica surfaces irrespective of the added polymer concentration, suggesting a strong adsorption of the copolymer on the surface. The medium (f p = 40%) and high (f p = 70%) charge density copolymers, on the other hand, provided an adhesive bridging attraction at low polymer concentrations, but a purely repulsive force at higher polymer concentrations. The range of these repulsive forces, however, was significantly smaller than that measured for the low charge density polymer. The medium and high charge densities exhibit nearly an identical behavior in controlling the intersurface forces, although the forces are different with respect to magnitude. The flocculation tests follow the same trend as that of force–distance data, where a complete, a partial, and no flocculation observed with high, medium, and low charge density polymers, respectively. In all the cases, the range of surface interactions can be correlated with the polymer chain dimension corresponding to the fast diffusion process (individual chains) obtained from dynamic light‐scattering measurements. Mean‐field models proposed for charged polymers can qualitatively explain both the dependency of bridging interactions on polymer charge density and the dependency of force–distance profiles on added polymer concentrations. Finally, a mean‐field model was used quantitatively to account for the measured electrosteric interactions and their dependency on polymer charge density. © 2004 American Institute of Chemical Engineers AIChE J, 50: 2613–2626, 2004
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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".