Conjugated Polymers with Immolative Side Chains Enable Conductive, Flexible, Transparent Carbon Nanotube Films
Bibliographic record
Abstract
Single-walled carbon nanotubes (SWNTs) are promising materials for building transparent conducting films (TCFs). Nevertheless, commercially available SWNTs exhibit low purity and poor solubility. Conjugated polymers (CPs) have been widely reported to disperse SWNTs in organic solvents; however, converting CP-SWNT dispersions into TCFs has never been investigated. In this study, we used the poly(fluorene- co -phenylene) CP with self-immolative linkers (SILs) within its side chains to disperse SWNTs. The SIL enables clean and fast side chain removal from the CP-SWNT complex upon simple treatment with tetra- n -butylammonium fluoride (TBAF) and subsequently decreases the sheet resistance ( R s ) of the CP-SWNT thin films. We explored a highly reproducible method to manufacture CP-SWNT-TCFs on a Mylar substrate. All CP-SWNT-TCFs showed a significant decrease in R s post TBAF treatment, suggesting that eliminating the side chain can decrease R s while preserving %transmittance. Notably, these CP-SWNT-TCF films exhibited consistent R s across various bending radii and after 200 bending cycles, highlighting their applicability in flexible electronics. This proof-of-concept study opens up avenues to produce CP-SWNT-TCF and further enhance their electrical conductivity by removing CP side chains.
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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".