Improving the photoluminescence quantum efficiency of size-tunable, solution-processed lead-sulfide quantum dots in film
Bibliographic record
Abstract
This work shows that reducing the concentration of nanocrystals in polymer significantly improves the PLQE of polymer/nanocrystal films. It shows that forming films in the presence of an abundance of passivating organic molecules also results in a high PLQE. This work improves the PLQE of nanocrystals in film from less than 1% to above 10%. Lead-sulfide (PbS) nanocrystals have high photoluminescence quantum efficiency (PLQE) when synthesized in solution (30%). When those same nanocrystals are made into a film, the PLQE drops significantly. Since practical nanocrystal devices will employ nanocrystals in film, it is essential to improve their PLQE. It is also important to understand what factors influence the PLQE of nanocrystals in films. This thesis also explores the effect of solvent, passivating ligand, pump intensity, and constant illumination on the PLQE of nanocrystals in film and solution.
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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".