Responsive morphology transition from micelles to vesicles based on dynamic covalent surfactants
Bibliographic record
Abstract
A dynamic covalent bond is widely used to fabricate stimuli responsive systems due to its reversible molecular recognition properties. In this study, we developed a pH-responsive morphology transition system based on a mixture of a cationic surfactant CTAB and two nonamphiphilic precursors, 4-hydroxybenzaldehyde (HB) and octylamine (OA), at a molar ratio of 100 : 60 : 60 (CTAB/HB/OA). The morphology transition of CTAB/HB/OA was characterized by 1H NMR spectroscopy, Fourier transform infrared spectroscopy, macroscopic appearance observation, dynamic light scattering, and rheological and cryo-TEM measurements. The phase behavior of CTAB/HB/OA solutions underwent transition from a water-like fluid to a transparent gel-like solution and then converted into a turbid low-viscosity solution upon increasing the pH. Upon increasing the pH from 4.93 to 7.99, the morphology was transformed from spherical micelles to wormlike micelles. Upon further increasing the pH to 12.02, the wormlike micelles gradually disappeared with the formation of vesicles. Thus, a morphology transition from micelles to vesicles can be triggered by varying the pH of CTAB/HB/OA solutions. This drastic variation in morphology behavior was attributed to the pH dependent ionization and formation of the anionic surfactant HB-OA-. Besides, over 3 cycles of morphological alternation among spherical micelles, wormlike micelles and vesicles of the CTAB/HB/OA solutions can be obtained by adjusting the pH.
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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) | 0.000 | 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".