Mixed-quantum-dot solar cells
Bibliographic record
Abstract
Colloidal quantum dots are emerging solution-processed materials for large-scale and low-cost photovoltaics. The recent advent of quantum dot inks has overcome the prior need for solid-state exchanges that previously added cost, complexity, and morphological disruption to the quantum dot solid. Unfortunately, these inks remain limited by the photocarrier diffusion length. Here we devise a strategy based on n- and p-type ligands that judiciously shifts the quantum dot band alignment. It leads to ink-based materials that retain the independent surface functionalization of quantum dots, and it creates distinguishable donor and acceptor domains for bulk heterojunctions. Interdot carrier transfer and exciton dissociation studies confirm efficient charge separation at the nanoscale interfaces between the two classes of quantum dots. We fabricate the first mixed-quantum-dot solar cells and achieve a power conversion of 10.4%, which surpasses the performance of previously reported bulk heterojunction quantum dot devices fully two-fold, indicating the potential of the mixed-quantum-dot approach.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".