Gels of Semiconducting Polymers in Benign Solvents
Bibliographic record
Abstract
Gels of semiconducting polymers have many potential applications, including biomedical devices and sensors. Here, we report a self-assembled gel system consisting of isoindigo-based semiconducting polymers with galactose side chains in benign, alcohol-based solvents. Because of the carbohydrate side chains, the modified isoindigo polymers are soluble in alcohols. We obtained thermoreversible gels in 1-propanol using these polymers and di-Fmoc-l-lysine, a molecular gelator. The polymers and molecular gelators have been selected in such a way that they do not have significant physical interactions. The molecular gelator self-assembled to form a fibrous structure that confines the polymer chains in the interstitial spaces of the fibers. The polymer chains formed local aggregations and increased the shear moduli of the gels significantly. Bulky galactose side chains and the less planar nature of the polymer backbone hindered the formation of long-range assembled structures of the polymers. However, the dispersion of polymers throughout the gel samples resulted in a percolated structure in the dried gel films. The bulk electrical conductivity of dried gels confirmed the presence of such percolated structures. Our results demonstrated that carbohydrate-containing conjugated polymers can be combined with molecular gelators to obtain gels in eco-friendly solvents.
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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) | 0.001 | 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 | 0.001 |
| 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".