Influence of Polymer Electronics on Selective Dispersion of Single‐Walled Carbon Nanotubes
Bibliographic record
Abstract
The separation and isolation of semiconducting and metallic single-walled carbon nanotubes (SWNTs) on a large scale remains a barrier to many commercial applications. Selective extraction of semiconducting SWNTs by wrapping and dispersion with conjugated polymers has been demonstrated to be effective, but the structural parameters of conjugated polymers that dictate selectivity are poorly understood. Here, we report nanotube dispersions with a poly(fluorene-co-pyridine) copolymer and its cationic methylated derivative, and show that electron-deficient conjugated π-systems bias the dispersion selectivity toward metallic SWNTs. Differentiation of semiconducting and metallic SWNT populations was carried out by a combination of UV/Vis-NIR absorption spectroscopy, Raman spectroscopy, fluorescence spectroscopy, and electrical conductivity measurements. These results provide new insight into the rational design of conjugated polymers for the selective dispersion of metallic SWNTs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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 teacher head, 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".