Doping Poly(3-hexylthiophene) Nanowires with Selenophene Increases the Performance of Polymer-Nanowire Solar Cells
Bibliographic record
Abstract
Abstract Developing novel materials analogous to poly(3-hexylthiophene) (P3HT) with increased absorption range and good one-dimensional self-assembly properties should increase photovoltaic performance while taking advantage of the well-established structure–property relationships developed for P3HT. Herein, we have fabricated novel polymer nanowires composed of P3HT doped with varying amounts of selenophene. Doping is accomplished by statistical polymerization and results in the incorporation of selenophene into the P3HT crystal lattice. Selenophene doping increases optical absorption far beyond what can be achieved by simply blending two materials. Polymer nanowire solar cells using selenphene-doped P3HT outperform native P3HT nanowire and corresponding ternary blend solar cells, reaching an overall maximum performance of >4% PCE. These are some of the highest values of any polymer nanowire solar cells and show that the selenophene-doping strategy is important for achieving high-performance devices.
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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".