Functionalization of Single-Walled Carbon Nanotubes with Well-Defined Polystyrene by “Click” Coupling
Bibliographic record
Abstract
Covalent functionalization of alkyne-decorated SWNTs with well-defined, azide-terminated polystyrene polymers was accomplished by the Cu(I)-catalyzed [3 + 2] Huisgen cycloaddition. This reaction was found to be extremely efficient in producing organosoluble polymer-nanotube conjugates, even at relatively low reaction temperatures (60 degrees C) and short reaction times (24 h). The reaction was found to be most effective when a CuI catalyst was employed in the presence of 1,8-diazabicyclo[5.4.0]undec-7-ene as an additive. IR spectroscopy was utilized to follow the introduction and consumption of alkyne groups on the SWNTs, and Raman spectroscopy evidenced the conversion of a high proportion of sp(2) carbons to sp(3) hybridization during alkyne introduction. Thermogravimetric analysis indicated that the polymer-functionalized SWNTs consisted of 45% polymer, amounting to approximately one polymer chain for every 200-700 carbons of the nanotubes, depending on polymer molecular weight. Transmission electron microscopy and atomic force microscopy were utilized to image polymer-functionalized SWNTs, showing relatively uniform polymer coatings present on the surface of individual, debundled nanotubes.
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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".