Interactions of carbon nanotubes with pyrene‐functionalized linear‐dendritic hybrid polymers
Bibliographic record
Abstract
Abstract A series of linear‐dendritic hybrid polymers, containing pyrene units at the periphery of aliphatic polyester dendrons, were prepared for the purpose of dispersing shortened single‐walled carbon nanotubes (SWNTs) in tetrahydrofuran (THF). The prepared hybrids contained 1, 2, 4, 8, or 16 (G0 through G4) pyrene units and a linear segment composed of polystyrene. It was found that a minimum of four pyrene units was necessary to form a strong enough interaction with SWNTs to enable steric stabilization in solution, when using a linear polymer segment of 11.5 kDa. Increasing either the number of pyrene units per polymer chain or the length of the polymer segment to 18.0 kDa did not improve nanotube solubility, whereas decreasing the polymer length resulted in significantly less effective nanotube dissolution. The G4 dendron alone, without the linear polystyrene segment, was also found to impart solubility to the nanotubes in THF. Interactions between the series of linear‐dendritic hybrids and full‐length multiwalled carbon nanotubes were also investigated, and it was found that the polymers exhibited strong interactions with the multiwalled carbon nanotube surface, resulting in the formation of stable solutions. © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 48: 1016–1028, 2010
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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".