Self-Assembled Structures of Giant Surfactants Exhibit a Remarkable Sensitivity on Chemical Compositions and Topologies for Tailoring Sub-10 nm Nanostructures
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Bibliographic record
Abstract
We report a remarkable sensitivity of self-assembled structures of giant surfactants on their chemical compositions and molecular topology, which facilitate the engineering of various nanophase-separated structures with sub-10 nm feature sizes. Two classes of giant surfactants composed of various functionalized polyhedral oligomeric silsesquioxane (POSS) heads tethered with one or two polystyrene (PS) tails were efficiently prepared from common precursors of vinyl-substituted POSS–PS conjugates via one-step “thiol–ene” postpolymerization functionalization. With identical molecular weights of the PS tails, the resulting giant surfactants exhibited distinct highly ordered phases, as evidenced by small-angle X-ray scattering and transmission electron microscopy observations. Moreover, comparison between the topological isomers revealed that the self-assembled structures are also highly sensitive to molecular topology. Introduction of two PS tails with half-length not only shifted the boundaries between different ordered phases but also altered the packing configurations of the functional POSS cages, leading to further reduced feature sizes of the self-assembled nanodomains. Interestingly, a lower order–disorder transition temperature was also observed in the fluorinated F 13 POSS tethered with two PS 17 tails, compared to its topological isomer composed of F 13 POSS tethered with one PS 35 tail, indicating that the topological effect also existed in phase transition behaviors. These results provide insights to rationally design and precisely tailor self-assembled structures by controlling both primary chemical compositions and molecular topology in POSS-based giant surfactants.
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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 it