Controlled synthesis of near-infrared quantum dots for optoelectronic devices
Bibliographic record
Abstract
We designed a facile approach for the synthesis of PbS quantum dots (QDs) using thiourea and lead acetate as sources of sulfur and lead, respectively. The sizes of the PbS QDs could be systematically controlled by simply adjusting the reaction parameters. Cd post-treatment via a cation exchange method was performed to increase the stability of QDs. As a proof of concept, colloidal PbS QDs synthesized by using air-stable thiourea were employed as light harvesters for both (i) solar driven photoelectrochemical (PEC) hydrogen generation and (ii) QDs sensitized solar cells (QDSSCs). For PEC hydrogen generation, similar saturated photocurrent densities are observed by using thiourea compared to bis(trimethylsilyl) sulfide, which is air-sensitive and unstable. For QDSSCs, the devices fabricated with QDs synthesized from thiourea reveal a better performance compared to devices fabricated with QDs synthesized from traditional bis(trimethylsilyl) sulfide. Our work demonstrates that this synthetic method is a promising alternative to the existing methodologies of PbS QDs and holds great potential for future solar technologies.
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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".