Are substitutes to Cd-based quantum dots in displays more sustainable, effective, and cost competitive? An alternatives assessment approach
Bibliographic record
Abstract
Light emissive organics and inorganic nanoparticles are substance classes competing for applications in displays in the form of organic LEDs (OLEDs) and quantum LEDs (QLEDs), respectively. Upcoming substance classes (perovskites) and Q-OLED displays also contain novel nanomaterials and organics for these applications. However, the sustainability of these emissive substances is difficult to assess quickly and broadly because of their complexity, their inherently different structures, and their rapid evolution in the literature. We propose the use of an alternatives assessment to compare the hazard, cost, and performance of these competing substances, with a focus on replacing cadmium-containing quantum dots. The cost assessment highlights competitiveness of OLEDs because of their low amounts needed per display, but performance assessments do not identify a preferred alternative. The hazard results indicate there is no clear alternative either, with each novel nanomaterial or organic substance having different negative aspects. These results identify the need for a low-hazard high-performing alternative substance, and the assessment provides a framework for researchers to evaluate their own novel substances.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".