The Critical Role of Electron‐Donating Thiophene Groups on the Mechanical and Thermal Properties of Donor–Acceptor Semiconducting Polymers
Bibliographic record
Abstract
Abstract Organic semiconducting donor–acceptor polymers are promising candidates for stretchable electronics owing to their mechanical compliance. However, the effect of the electron‐donating thiophene group on the thermomechanical properties of conjugated polymers has not been carefully studied. Here, thin‐film mechanical properties are investigated for diketopyrrolopyrrole (DPP)‐based conjugated polymers with varying numbers of isolated thiophene moieties and sizes of fused thiophene rings in the polymer backbone. Interestingly, it is found that these thiophene units act as an antiplasticizer, where more isolated thiophene rings or bigger fused rings result in an increased glass transition temperature ( T g ) of the polymer backbone, and consequently elastic modulus of the respective DPP polymers. Detailed morphological studies suggests that all samples show similar semicrystalline morphology. This antiplasticization effect also exists in para ‐azaquinodimethane‐based conjugated polymers, indicating that this can be a general trend for various conjugated polymer systems. Using the knowledge gained above, a new DPP‐based polymer with increased alkyl side chain density through attaching alky chains to the thiophene unit is engineered. The new DPP polymer demonstrates a record low T g , and 50% lower elastic modulus than a reference polymer without side‐chain decorated on the thiophene unit. This work provides a general design rule for making low‐ T g 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".