Wide Bandgap Polymer Donors Containing Dihalovinyl Thiophene Building Blocks for Organic Solar Cells
Bibliographic record
Abstract
This work presents the development of two novel gem -dihalovinyl thiophene-based building blocks, namely 3-(2,2-difluorovinyl)thiophene (TDF) and 3-(2,2-dichlorovinyl)thiophene (TDCl), for constructing cost-effective wide bandgap polymer donors for organic solar cells (OSCs) based on narrow bandgap nonfullerene acceptors (NFAs). Two polymers, PBDT-TDF and PBDT-TDCl, have been synthesized using these building blocks. Both polymers have energy levels that match the NFA Y6. The OSC device with PBDT-TDF:Y6 has achieved a power conversion efficiency (PCE) of 8.83%. In contrast, the PBDT-TDCl:Y6-based device has a higher PCE of 11.02% due to the increased short-circuit current density. The improved charge transport ability in the PBDT-TDCl:Y6 blend film plays a vital role in enhancing the overall solar cell performance. An interesting observation is that the bulkier dichlorovinyl moiety seems to induce a conformational locking effect, effectively maintaining a higher extent of coplanarity in the polymer backbone. This effect contributes to the elevated hole mobility observed in PBDT-TDCl, in comparison to PBDT-TDF. These findings highlight the promising potential of these gem -dihalovinyl thiophenes as cost-effective building blocks for the growth of polymer semiconductors for solar cells and other printed electronics utilization.
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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".