Transfert biomimétique : de la luciole vers la diode électroluminescente
Bibliographic record
Abstract
Autrefois reléguées à des marchés ciblés et de faible volume, les diodes électroluminescentes (DELs) révolutionnent toutefois déjà le monde de lâéclairage grâce à la spectaculaire croissance de leur efficacité énergétique et leur durée de vie record. Les projections annoncent des avancées technologiques majeures concernant les DELs dâici à 2025 [1]. Cependant, plusieurs problèmes technologiques limitent lâefficacité dâextraction de photons des DELs émettant sous les 400 nm en raison de lâemplacement de la zone radiative : se trouvant à lâintérieur du semiconducteur, une fraction considérable de photons (95%) reste piégée au sein de la diode à cause de la réflexion totale interne [2]. Le CRN2 possède toutes les infrastructures nécessaires pour la fabrication de DELs bleues et UV. De la photolithographie à la gravure de type ICP du nitrure de gallium (GaN), plusieurs techniques de fabrications ont été mises au point pour lâélaboration de DELs. Un solide procédé est disponible à lâUniversité de Sherbrooke permettant ainsi lâétude de lâextraction de la lumière de DELs optimisées au sein dâune collaboration internationale.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".