Selenophene and Thiophene-Based Conjugated Polymer Gels
Bibliographic record
Abstract
Conjugated polymer gels are promising materials that are intrinsically stretchable and conductive, which may play an important role in the development of stretchable electronics. In this work, a series of thiophene and selenophene-based conjugated polymers with similar molecular weight and low dispersity were synthesized and the gelation conditions of these polymers were studied. The electrical performance of both thin and bulk films of these conjugated polymer gels were investigated. Blade-coated gels that form the highest quality films can achieve a similar charge carrier mobility as a spin coated sample, showing that gels are indeed promising electronic materials. The most promising gels were studied as a stretchable device. The initial application of strain appears to lead to the lower mobility; however, the device stabilizes and retains the same mobility from 18% to 40% strain. Finally, a new cycle-doping method was developed to successfully dope the bulk gels to yield conductive films. This method allows one to monitor the changes in conductivity as a function of doping to ultimately achieve the highest conductivity. The cycle-doping method appears to be superior to the commonly used dip-doping method. Overall this work expands on the types of conjugated polymers gels that are useful for electronics, stretchable electronics, and conductive materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".