Interaction of PBMA Latex Particles with Nonionic Surfactants in Aqueous Solution
Bibliographic record
Abstract
The interaction between poly(butyl methacrylate) (PBMA) latex particles of different size and nonylphenol surfactants containing poly(ethylene oxide) chains (NP-EO x ) of different lengths was studied by titration microcalorimetry. Three systems, 393 nm PBMA latex + NP-20, 141 nm PBMA latex + NP-20 and 393 nm PBMA latex + NP-40, were investigated. In each case the binding can be described by Langmuir type isotherms, which suggests that the dominant interaction is that of the hydrophobic portion of the surfactant with the PBMA latex surface. To differentiate the heat effects caused by adsorption from those caused by dilution of the surfactant, corrected dilution enthalpy curves were calculated. These, in turn, were used for the preparation of the net adsorption enthalpy and differential molar enthalpy of adsorption curves. The net enthalpy curves for the three systems examined have much in common. The interaction between the surfactants and the PBMA latex was endothermic over the whole range of surfactant concentrations. Thus the adsorption of NP-20 and NP-40 onto PBMA latex particles is an entropy driven process. Our results can be compared with the literature data [ Int. Journal of Pharmaceutics 1993, 89, 33] on the adsorption of nonylphenol surfactants on polystyrene latex, which, unlike our systems, is characterized by a significant exothermic effect at low values of surface coverage.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".