Physical and optical properties of weakly charged polyelectrolyte multilayer films by Ozzy Mermut.
Bibliographic record
Abstract
Thin multilayer films were prepared through layer-by-layer adsorption of oppositely charged polyelectrolytes in aqueous media using a recently established electrostatic self-assembly approach. The adsorbing polyelectrolytes can be classified as either weak or strong based on their level of dissociation in solution. The density of charge in weakly charged polyelectrolytes, unlike in strongly charged ones, can be controlled by adjusting the solution pH about the value of its dissociation constant. At the onset of this dissertation, there were some fundamental and unresolved questions regarding assembly mechanisms, kinetics, and internal structures of the layers in polyelectrolyte multilayer films (PEMs). The studies here examine how varying the level of dissociation of polyelectrolytes in solution influences the kinetics of assembly, and adsorption behavior, as well as some structural, mechanical, and optical properties of PEMs. Using mainly ellipsometry, fluorescence, UV-vis spectrophotometry, and atomic force microscopy (used as a nanoindentation tool), the following investigations of weakly charged polyelectrolytes in multilayer assemblies were performed:
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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) | 0.004 | 0.001 |
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".