Poly(3-hexylthiophene)-<i>stat</i>-poly(3-dodecylselenophenes): Conjugated Statistical Copolymers and Their Gels
Bibliographic record
Abstract
The molecular weight of conjugated polymers plays an important role in polymer self-assembly, which has a significant influence on their application in electronics. In this work, we report the self-assembly behavior of poly(3-hexylthiophene)- stat -poly(3-dodecylselenophenes) as both thin films and organogels at low, medium, and high degrees of polymerization. Different self-assembly behaviors are observed in pristine copolymer films, annealed copolymer films, and copolymer gels. We found that through cycle-doping, a process by which the sample is gelled and repetitively doped by solution, conjugated statistical copolymer gels have greater conductivities compared to thin films of the same polymers and maintain high conductivities after seven cycles of doping. Statistical copolymer gels at medium and high degrees of polymerization show the greatest conductivity, which is likely due to their unique morphology from that of the low degree of polymerization. Grazing incident wide-angle X-ray scattering suggests an inter charge transfer doping mechanism takes place between the polymer and dopant.
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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".