Crosslinking Poly(Tetrazine) Decorated Single‐Walled Carbon Nanotubes via Inverse Electron Demand Diels‐Alder Reaction for Film Fabrication
Bibliographic record
Abstract
ABSTRACT Thin films of single‐walled carbon nanotubes (SWNTs) were produced by first dispersing them using a conjugated poly(tetrazine) polymer wrapper, followed by filtration through a teflon membrane. The tetrazine units of the polymer wrapper are highly reactive toward trans‐cyclooctene (TCO) via the inverse‐electron‐demand Diels‐Alder (IEDDA) reaction. This reactivity allows crosslinking of the SWNT film post‐fabrication by using a crosslinker bearing multiple TCO groups. A series of polyethylene glycol (PEG) crosslinkers of different lengths with trans‐cyclooctene (TCO) end‐groups was synthesized and used to crosslink the SWNT films. Characterization of the crosslinking chemistry was carried out using scanning electron microscopy as well as FTIR and Raman spectroscopy, providing evidence for crosslink formation. Bulk and surface mechanical properties of the resulting films were studied using a home‐built mechanical analyzer as well as quantitative nanomechanical mapping using an atomic force microscope. These studies showed that crosslinked films exhibit a lower modulus, indicating a reduction in film stiffness post‐crosslinking. Overall, these studies demonstrate the utility of the IEDDA reaction in forming free‐standing, crosslinked films of polymer‐decorated SWNTs.
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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".