Hydrophobic polythiophene hole-transport layers to address the moisture-induced decomposition problem of perovskite solar cells
Bibliographic record
Abstract
Perovskite solar cells have emerged as one of the most promising next-generation photovoltaic technologies and have achieved a record power conversion efficiency of 22.7%. The technology meets industrial demands for cost effectiveness and scalability; however, the instability of lead halide perovskites toward moisture is a major barrier to their commercial development. Previous studies have revealed that the use of hydrophobic hole-transport layers (e.g., poly(3-hexylthiophene), P3HT) can slow the ingress of water vapor and improve the lifetime of the underlying perovskite, suggesting a route to longer lived devices. In this work, we report the synthesis of a variety of poly(3-alkoxythiophenes) with different side chains. The side chains range from hydrophilic (triethylene glycol methyl ether) to extremely hydrophobic (highly fluorinated hexyloxy). We evaluated the polymers, alongside commercially available P3HT, for their ability to stabilize methylammonium lead iodide films at high relative humidities. The fluorinated polythiophenes were able to substantially improve the perovskite lifetime, suggesting that more hydrophobic hole-transport layers may be a route to more stable perovskite solar cells.
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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".