NMR Study of the Dissolution of Core-Crystalline Micelles
Bibliographic record
Abstract
Short fragments of the core-crystalline micelles formed by a sample of poly(ferrocenyldimethylsilane)-block-poly(isoprene) (PFS-b-PI) block copolymer (BCP) underwent self-seeding in decane when heated above its dissolution temperature. Variable temperature (VT) 1H NMR and diffusion-ordered pulsed-gradient spin–echo (DOSY) NMR were used to monitor the behavior of micelles that dissolved as a function of increasing temperature. We examined a sample of micelle fragments of PFS65-b-PI637 characterized by Ln = 39 nm and Lw/Ln = 1.13. The PI corona had high mobility and gave a 1H NMR signal in both micellar and unimer forms. In contrast, the PFS component could only be detected for the dissolved unimer. We found from 1H NMR that essentially all the BCP molecules were incorporated into the micelles at temperatures up to and including 50 °C, at the limit of NMR detection. Both PFS and PI resonances could be detected between 70 and 100 °C, and the integration ratio of the PFS-to-PI peaks increased with temperature. DOSY NMR measured the self-diffusion coefficients (Ds) of the micelle fragments and unimer at these temperatures. The hydrodynamic radii (Rh) for these species were calculated from Ds using the Stokes–Einstein equation. The PFS signals gave Rh values in the range of 5–6 nm at temperatures between 80 and 100 °C, consistent with unimer diffusion. PI signals were fitted by an exponential decay at 25 °C with Rh = 38 nm characteristic of the micelle fragments and at 90, 95, and 100 °C with Rh ≈ 6 nm, corresponding to unimer. At intermediate temperatures (70–85 °C), PI signals were fitted to a sum of two exponential terms, consistent with a fast diffusing species and a slow diffusing species. Interestingly, we noticed that the size of the micelle fragments at elevated temperatures (80 and 85 °C) was sensitive to sample history; samples heated directly to the elevated temperatures were found to be shorter than those heated stepwise.
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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".