Hierarchical Polymer–Carbon Nanotube Hybrid Mesostructures by Crystallization-Driven Self-Assembly
Bibliographic record
Abstract
Multistep crystallization-driven self-assembly has great potential to enable the construction of sophisticated hybrid mesostructures. During the assembly procedure, each step modifies the properties of the overall structure. Here, we demonstrate the flexibility and efficiency of this approach by preparing polymer-carbon nanotube (CNT) hybrid mesostructures. We started by growing polyferrocenyldimethylsilane (PFS) homopolymer crystals onto multiwalled CNTs. This first step facilitated the redispersion of the coated CNTs in both polar (2-propanol) and nonpolar (decane) solvents. In the second step of hybrid construction, a unimer solution of a PFS block copolymer was added into the PFS-CNT solution. The PFS coating on the CNT initiated the growth of elongated micelles, resulting in structures that resembled hairy caterpillars. PFS-b-P2VP (P2VP = poly-2-vinylpyridine) micelles were grown from the surface of PFS-CNT hybrids in 2-propanol, and PFS-b-PI (PI = polyisoprene) micelles were grown from these hybrids in decane. These micelles, by transmission electron microscopy were seen to have an unusual wavy kinked structure, very different from the uniform smooth structures normally formed by both block copolymers. For hybrids with PFS-b-PI micelles, cross-linking of the micelle coronas locked the whole structure in place and allowed us to use the partial oxidation of PFS components to grow metal nanoparticles in the core of these micelles. We finally investigated the influence of the corona-forming block used to grow the micelles on the wettability of films made from these mesostructures. Films formed with CNT hybrids grafted with PFS-b-PI micelles were superhydrophobic (contact angle, 152°). In contrast, the surface of the films was much more hydrophilic (contact angle, 54°) when they were prepared from CNT hybrids grafted with PFS-b-P2VP micelles.
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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 | 0.001 | 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".