Enhanced Mobility-Lifetime Products in PbS Colloidal Quantum Dot Photovoltaics
Bibliographic record
Abstract
Colloidal quantum dot (CQD) photovoltaics offer a promising approach to harvest the near-IR region of the solar spectrum, where half of the sun's power reaching the earth resides. High external quantum efficiencies have been obtained in the visible region in lead chalcogenide CQD photovoltaics. However, the corresponding efficiencies for band gap radiation in the near-infrared lag behind because the thickness of CQD photovoltaic layers from which charge carriers can be extracted is limited by short carrier diffusion lengths. Here, we investigate, using a combination of electrical and optical characterization techniques, ligand passivation strategies aimed at tuning the density and energetic distribution of charge trap states at PbS nanocrystal surfaces. Electrical and optical measurements reveal a more than 7-fold enhancement of the mobility-lifetime product of PbS CQD films treated with 3-mercaptopropionic acid (MPA) in comparison to traditional organic passivation strategies that have been examined in the literature. We show by direct head-to-head comparison that the greater mobility-lifetime products of MPA-treated devices enable markedly greater short-circuit current and higher power conversion efficiency under AM1.5 illumination. Our findings highlight the importance of selecting ligand treatment strategies capable of passivating a diversity of surface states to enable shallower and lower density trap distributions for better transport and more efficient CQD 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".