Direct Measurements of Interactions between Hydrophobically Anchored Strongly Charged Polyelectrolyte Brushes
Bibliographic record
Abstract
We investigated the nature and the range of interactions between negatively charged polyelectrolyte-coated surfaces as a function of salt concentration using the surface forces apparatus. The measured force profiles (interaction forces versus separation distance) are purely repulsive and show long-range electrostatic and short-range steric interactions. The measured range of interaction in salt-free as well as in low ionic strengths extends well beyond the contour length of the polyelectrolyte chain. It is shown that the interaction range between the ionic brush layers and the grafting density depend on the ionic strength of the solution. In salt-free solution, the counterions associated with polyelectrolyte cause the chains to stretch and give rise to long-range double-layer electrostatic repulsions between the opposing chains. When salt is added to the system, the electrostatic interactions are partially screened and the polymer chain regains its flexibility and therefore the range of interactions is reduced. The measured total range of interaction exhibits relatively weaker dependence on the salt concentration. We find that our force−distance profiles with added salt in a compressed regime can be very well described by the Pincus scaling model.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".