Colloidal quantum dot materials for next-generation near-infrared optoelectronics
Bibliographic record
Abstract
Colloidal quantum dots (CQDs) are a promising class of materials for next-generation optoelectronic devices, such as displays, LEDs, lasers, photodetectors, and solar cells. CQDs can be obtained at low cost and in large quantities using wet chemistry. CQDs have also been produced using various materials, such as CdSe, InP, perovskites, PbS, PbSe, and InAs. Some of these CQD materials absorb and emit photons in the visible region, making them excellent candidates for displays and LEDs, while others interact with low-energy photons in the near-infrared (NIR) region and are intensively utilized in NIR lasers, NIR photodetectors, and solar cells. In this review, we have focused on NIR CQD materials and reviewed the development of CQD materials for solar cells, NIR lasers, and NIR photodetectors since the first set of reports on CQD materials in these particular applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".