(Invited) Realizing Narrow Bandwidth Visible Photoluminescence from Colloidal Silicon Quantum Dots
Bibliographic record
Abstract
Quantum dot light-emitting diodes (QD-LEDs) are an attractive alternative to organic light-emitting diodes (OLEDs) that have attracted attention for next generation optoelectronic devices due to their high colour-saturated photoluminescence, processability, and stability. Existing QD-LEDs often employ toxic or rare metals (e.g., Cd, Pb, In, etc.). Although colloidal silicon quantum dots (SiQDs) are an attractive alternative because of their abundance, biocompatibility and tailorable surface chemistry, tuning their luminescence throughout the visible spectrum can be challenging. Furthermore, SiQD emission shows a comparatively wide bandwidth that is a consequence of the inherent properties of the Si band structure. As a result the narrowing SiQD luminescence is not readily achieved by straightforward size selection methods used for other quantum dots. One alternative approach is to prepare optical cavities that preferentially select specific emission wavelengths using optical structures. This presentation will outline our investigations targeted on realizing bright, high quantum yield, narrow bandwidth luminescence from SiQD-polymer hybrids.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.009 |
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".