Interactions between Hydrophobically Modified Alkali-Swellable Emulsion Polymers and Sodium Dodecyl Sulfate Probed by Fluorescence and Rheology
Bibliographic record
Abstract
The interactions between a pyrene-labeled hydrophobically modified alkali-swellable emulsion (Py-HASE) polymer and the anionic surfactant sodium dodecyl sulfate (SDS) in aqueous solution were investigated with a fluorometer, a rheometer, and a combination of both instruments to probe the fluorescence of the polymer while the solution was being sheared. Different amounts of SDS were added to two solutions with Py-HASE concentrations of 8 and 57 g/L. The pyrene monomer and excimer decays of the Py-HASE solutions were acquired and globally fitted according to the fluorescence blob model (FBM) and the model free (MF) analysis. Both models yielded the same molar fractions of pyrenes that were isolated, aggregated, or forming excimer by diffusion. The average number of pyrenes per micelle, <n>, was determined according to the FBM and found to equal 2.0 at the SDS concentration corresponding to a maximum in solution viscosity. For a Py-HASE concentration of 57 g/L, the solution viscosities at different SDS concentrations were measured from the Newtonian plateau regions and were found to peak at an SDS concentration of 11 mM. The steady-state fluorescence spectra were acquired at SDS concentrations of 0.1, 6.0, 11.1, and 17 mM while the 57 g/L Py-HASE solution was sheared. Although the solutions of Py-HASE and SDS were found to shear-thin substantially with the solution viscosity decreasing by up to 4 orders of magnitude, no change was observed in the fluorescence spectra acquired at shear rates ranging from 0.005 to 500 s(-1). The overlap of the fluorescence spectra under conditions where the solution viscosity decreased by 4 orders of magnitude suggested that the rearrangement of the hydrophobes from inter- to intramolecular associations that leads to shear-thinning occurs on a time scale that is much faster than that over which the rheology experiments are being conducted.
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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".