Synergistic ligand exchange and UV curing of PbS quantum dots for effective surface passivation
Bibliographic record
Abstract
Lead sulfide (PbS) quantum dots (QDs) are promising materials in solution-processed photovoltaic (PV) devices due to their tunable bandgap and low-cost processing. Replacing the long oleic acid ligands of the as-synthesized QDs with shorter ligands is a key step for making functional QD PVs with correctly tuned band energies and reduced non-radiative recombination centers. In this work, we study the effect of ultraviolet (UV) treatment of PbS QD layers on the QD surface states during ligand exchange. We demonstrate that this straightforward approach effectively reduces the surface trap states and passivates the surface of QDs. We find that UV treatment reduces the density of hydroxyl groups attached to the QD surface and improves the bonding of short ligands to the QD surface. Multiple analyses show the reduction of nonradiative recombination centers for the UV-treated sample. The power conversion efficiency (PCE) of our optimized PbS QD device reached 10.7% (vs. 9% for the control device) and was maintained above 10% after 230 h of constant illumination.
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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".