Reactive Strand Extension to Improve Stretchability in Semiconducting Polymers
Bibliographic record
Abstract
As electronics become more seamlessly integrated into our everyday lives, the demand for durable, stretchable, and electron-conducting materials will continue to grow. However, many conductive materials suffer from poor electrical performance under repeated mechanical strain, which limits their lifetime use. Inspired by developments to enhance stretchability in nonconjugated materials with covalent mechanochemistry, we explore reactive strand extension (RSE) as a strategy to mitigate poor electronic performance in conjugated polymer semiconductors under strain. Herein, we incorporated RSE into a donor–acceptor conjugated polymer by copolymerizing cinnamate dimers into the conjugated backbone and evaluated their impact on stretchability. RSE was found to improve stretchability in cross-linked conjugated polymer systems via crack onset strain measurements, atomic force microscopy, dichroic ratio measurements, and grazing-incidence wide-angle X-ray scattering. Lastly, charge carrier mobility measurements from organic field-effect transistors revealed that RSE-containing cross-linked conjugated polymers retained mobility more effectively under mechanical strain compared to unmodified conjugated polymers. Overall, our study presents an alternative strategy to improve the performance of conjugated polymers for stretchable electronics.
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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".