Efficient and Stable Colloidal Quantum Dot Solar Cells with a Green‐Solvent Hole‐Transport Layer
Bibliographic record
Abstract
Abstract Next‐generation solution‐processed solar cells will hopefully be processed using green solvents, and will unite high performance with operating stability. Colloidal quantum dot/polymer hybrid solar cells are of interest for their harvest of the visible as well as the near infrared; however, today's best polymer hole‐transporting layers (HTLs) rely on processing using hazardous solvents such as chlorobenzene. This stems from the strong polymer–polymer attraction in polymeric p‐type materials, which accounts for their limited solubility. Here, a new random polymeric HTL (asy‐ranPBTBDT) is reported that is soluble in green solvents such as 2‐methylanisole without compromising ultimate device power conversion efficiency. The new polymer structure induces a strong π–π stacking face‐on orientation and less lateral grain growth compared to control asy‐PBTBDT, leading to reduced charge recombination and improved device stability. The resulting device exhibits a power conversion efficiency (PCE) of 13.2% and retains 89% of its initial efficiency after 120 h of continuous device operation at the maximum power point, compared to a PCE of 11.4% and 71% degradation for control 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 | 0.001 |
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".