Lateral Growth of 1D Core-Crystalline Micelles upon Annealing in Solution
Bibliographic record
Abstract
The emergence of one-dimensional (1D) micelles obtained from the crystallization driven self-assembly (CDSA) in solution of crystalline-coil block copolymers has opened the door to the fabrication of a variety of sophisticated structures. While the development of these fascinating nanomaterials is blossoming, there is very little fundamental work dedicated to understanding the morphological evolution of these 1D micelles in solution. Here, using a combination of transmission electron microscopy, electron tomography, and static and dynamic light scattering, we studied the effect of annealing on a colloidal suspension of 1D micelle fragments formed by the self-assembly of a crystalline-coil poly(ferrocenyldimethylsilane)- block -poly(isoprene) (PFS- b -PI) block copolymer in decane, a solvent selective for PI. We are particularly interested in studying the evolution of the rectangular cross-section of the crystalline core of these micelle fragments. By electron tomography, we observed that the shorter dimension of the cross-section became even thinner upon annealing at elevated temperatures, while the longer dimension increased. In parallel, we observed an increase in packing density of the crystalline block as the fragments were annealed at temperatures above 60 °C. From these results, we concluded that annealing the micelle fragments induces a thinning of the crystalline core coupled with a lateral growth.
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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) | 0.001 | 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".