Soft and Stretchable Thienopyrroledione‐Based Polymers via Direct Arylation
Bibliographic record
Abstract
Abstract π ‐conjugated polymers (CPs) that are concurrently soft and stretchable are needed for deformable electronics. Molecular‐level modification of indacenodithiophene (IDT) copolymers, a class of CPs that exhibit high hole mobilities ( hole ), is an approach that can help realize intrinsically soft and stretchable CPs. Numerous examples of design strategies to adjust the stretchability of CPs exist, but imparting softness is comparatively less studied. In this study, a systematic molecular weight (MW) series is constructed on a promising candidate for soft CPs, poly(indacenodithiophene‐ co ‐thienopyrroledione) (p(IDT C16 ‐TPD C8 )), by optimizing direct arylation polymerization conditions in hopes of improving stretchability and μ hole without significantly impacting softness. We found p(IDT C16 ‐TPD C8 ) at a degree of polymerization of 32 shows high stretchability (crack onset strain, CoS > 100%) without significantly impacting softness (elastic modulus, E = 32 MPa), which to the best of our knowledge outperforms previously reported stretchable and soft CPs. To further study how molecular‐level modifications impact polymer properties, a MW series of a new extended donor unit polymer, poly(indacenodithienothiophene‐ co ‐thienopyrroledione) (p(IDTT C16 ‐TPD C8 )), was synthesized. The IDTT C16 copolymers did not result in a greater average μ hole when comparing between p(IDTT C16 ‐TPD C8 ) and p(IDT C16 ‐TPD C8 ) despite their higher crystallinity observed by GIWAXS. While these findings warrant further investigation, this study points toward unique charge transport properties of IDT‐based polymers.
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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".