Control Over Ligand Exchange Reactivity in Hole Transport Layer Enables High-Efficiency Colloidal Quantum Dot Solar Cells
Bibliographic record
Abstract
Colloidal quantum dot (CQD) solar cells are solution-processed photovoltaic devices that exhibit promise in harvesting the infrared solar spectrum. Solid-state ligand exchange is the method employed to fabricate the CQD hole transport layer (HTL) in these cells: insulating oleic acid ligands are substituted with short thiol ligands (1,2-ethanedithiol) to create conductive p-type CQD solids. Thiols’ high reactivity with the CQD surface results in rapid exchange, giving rise to aggregates of dots and unpassivated sites on dots, each contributing to sub-bandgap trap states. Here we report a strategy to minimize trap states in the CQD HTL by controlling the solvent type in the exchange. By employing a less volatile solvent, we achieve a slower reaction, leading to increased order and a 2 times reduced trap density in CQD solids. These improvements enable a power conversion efficiency of 13.1 ± 0.1% in CQD solar cells compared to control devices showing 12.4 ± 0.1%.
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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".