Supramolecular Functionalization of Single-Walled Carbon Nanotubes with Triply Fused Porphyrin Dimers: A Study of Structure–Property Relationships
Bibliographic record
Abstract
A triply fused porphyrin dimer bearing long alkyl chains for enhanced solubility was prepared and investigated for its ability to supramolecularly functionalize single-walled carbon nanotubes. It was found that this porphyrin dimer indeed binds strongly to the nanotube surface, allowing the removal of excess unbound porphyrin from solution without diminishing nanotube solubility. UV–vis spectroscopy indicated a bathochromic shift of the porphyrin Soret band upon binding to the nanotube surface, while Raman spectroscopy indicated that functionalization with the porphyrin dimer does not lead to any defects being formed on the nanotube wall. Transmission electron microscopy revealed the presence of individual nanotubes and small nanotube bundles that were heavily coated with porphyrin dimers. Comparison to analogous fused dimers bearing tert -butyl groups for solubility clearly demonstrated that long alkyl chains are necessary for prolonged solution stability of the nanotube complexes. While a previously investigated tert -butyl derivative was found to bind to the nanotube surface, the resulting complex precipitated out of solution within minutes. It was also found that the position of bulky substituents on the porphyrin dimer had a dramatic effect on whether it was able to interact with the nanotube surface.
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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".