Interactions in Water of Alkyl and Perfluoroalkyl Surfactants with Fluorocarbon- and Hydrocarbon-Modified Poly(<i>N</i>-isopropylacrylamides)
Bibliographic record
Abstract
Fluorescence spectroscopy and isothermal titration calorimetry (ITC) have been used to study the interactions in water at 25 degrees C of two anionic surfactants--sodium dodecyl sulfate (SDS) and sodium perfluorononanoate (SPFN)--with various pyrene-labeled hydrophobically modified poly(N-isopropylacrylamides) (HM-PNIPAM) grafted at random with small amounts of fluorocarbon chains (1H,1H-perfluorooctyl, CH2C7F15); (PNIPAM-F), or (n-octadecyl, C18H37) (PNIPAM-HPy) or both (PNIPAM-F/HPy). In aqueous solution, the copolymers form micellar structures consisting of a loose corona of hydrated poly(N-isopropylacrylamide) chains and a hydrophobic core rich in hydrocarbon or fluorocarbon groups. From fluorescence studies based on changes in the ratio of pyrene excimer to monomer emission intensity, it has been established (1) that mixed SDS/C18H37 clusters form along the polymer chain upon addition of SDS to either PNIPAM-HPy or PNIPAM-F/HPy and (2) that SPFN does not interact with the hydrocarbon-rich microdomains of the polymeric micelles. The conclusions were corroborated by ITC experiments, which yield the overall enthalpy change associated with polymer/surfactant interactions. They provided strong evidence (1) that SDS molecules adsorb along the PNIPAM main chain but do not mix with the fluorocarbon-rich microdomains of PNIPAM-F or PNIPAM-F/HPy and (2) that SPFN associates with the perfluorocarbon substituents of PNIPAM-F and PNIPAM-F/HPy but has a poor affinity for the polymer chain.
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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) | 0.001 | 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 | 0.000 |
| 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 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".