Design of Phosphor White Light Systems for High-Power Applications
Bibliographic record
Abstract
We developed a strategy that transforms phosphor down-converting white light sources from low-power systems into efficient high-power ones. To incorporate multiple phosphors, we generalized and extended a phosphor layer model, which we term CCAMP (color correction analysis for multiple phosphors). CCAMP describes both the scattering and saturation of phosphor materials and allows modeling of different layered structures. We employed a phosphor mixture comprising YAG:Ce and K 2 TiF 6:Mn 4+ to illustrate the effectiveness of the model. YAG:Ce’s high density and small particle size produce a large amount of scattering, while the long (4.8 ms) photoluminescent lifetime of K 2 TiF 6:Mn 4+ results in saturation at high pump power. By incorporating experimental photophysical results from the phosphors, we modeled our system and chose the design suitable for high-power applications. We report the first solid-state phosphor system that creates warm white light emission at powers up to 5 kW/cm 2 . Furthermore, at this high power, the system’s emission achieves the digital cinema initiative (DCI) requirements with a luminescence efficacy improvement of 20% over the stand-alone ceramic YAG:Ce phosphor.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".