Conductive, Monodisperse Polyaniline Nanofibers of Controlled Length Using Well‐Defined Cylindrical Block Copolymer Micelles as Templates
Bibliographic record
Abstract
Stable colloidal dispersions of polyaniline (PAni) nanofibers with controlled lengths from about 200 nm-1.1 μm and narrow length distributions (Lw/Ln < 1.04; Lw = weight average micelle length, Ln = number average micelle length) were prepared through the template-directed synthesis of PAni using monodisperse, solution-self-assembled, cylindrical, block copolymer micelles as nanoscale templates. These micelles were prepared through a crystallization-driven living self-assembly method from a poly(ferrocenyldimethylsilane)-b-poly(2-vinylpyridine) block copolymer (PFS25 -b-P2VP425). This material was initially self-assembled in iPrOH to form cylindrical micelles with a crystalline PFS core and a P2VP corona and lengths of up to several micrometers. Sonication of this sample then yielded short cylinders with average lengths of 90 nm and a broad length distribution (Lw/Ln = 1.32). Cylindrical micelles of PFS25 -b-P2VP425 with controlled lengths and narrow length distributions (Lw/Ln < 1.04) were subsequently prepared using thermal treatment at specific temperatures between 83.5 and 92.0 °C using a 1D self-seeding process. These samples were then employed in the template-directed synthesis of PAni nanofibers through a two-step procedure, where the micellar template was initially stabilised by deposition of an oligoaniline coating followed by addition of a polymeric acid dopant, resulting in PAni nanofibers in the emeraldine salt (ES) state. The ES-PAni nanofibers were shown to be conductive by scanning conductance microscopy, whereas the precursor PFS25-b-P2VP425 micelle templates were found to be dielectric in character.
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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".