Salt Effects on Solute Exchange and Micelle Fission in Sodium Dodecyl Sulfate Micelles below the Micelle-to-Rod Transition
Bibliographic record
Abstract
This paper describes micelle exchange kinetics of hydrophobic pyrene derivatives between SDS micelles in the presence of moderate concentrations of sodium counterions ([Na + ] < 150 mM). The kinetics were followed by fluorescence time-scan measurements in which the disappearance of excimer over time was monitored. The exchange rate constant k obs is highly sensitive to the counterion concentration and increases as a power law against [Na + ] with an exponent of 4, from a value of almost 0 in the absence of salt to 10 -2 s -1 for [Na + ] =100 mM. The exchange rate is not very sensitive to the concentration of SDS micelles, except as the SDS concentration affects the ionic strength, which indicates that the kinetics are dominated by a first-order process. This process is attributed to a fission−growth mechanism in which the fission rate is rate-limiting. Although fission can yield any size micelles, the use of hydrophobic probes restricts the observation to the events yielding two micelles large enough to bear the probe molecules. We propose that the barrier to fission is the creation of surface instabilities, which are enhanced in the proximity of the micelle-to-rod transition. Over the range of counterion concentrations investigated here, micelle fusion is inhibited by electrostatic repulsion.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".