UV-responsive CCD image sensors with enhanced inorganic phosphor coatings
Bibliographic record
Abstract
Typical polysilicon gate charge-coupled device (CCD) image sensors are unresponsive to ultraviolet (UV) light because of the high absorption of the radiation in polysilicon gate material, which leads to a short penetration depth (<2 nm), and absorption of the radiation in the gate material rather than within the channel of the CCD. An inorganic phosphor coating to convert the UV radiation to visible has been developed. Although the coating is similar to acrylics doped with organic laser dyes reported previously, in this work the organic dye has been replaced with a more robust inorganic phosphor. In addition, a new deposition method has been developed to improve the photoresponse nonuniformity (PRNU) of the coated sensor. The inorganic phosphor has been selected over organic laser dyes because organic molecules degrade rapidly upon exposure to UV radiation, with exponential degradation rates as high as 3% per hour at an illumination level of 1 /spl mu/W/cm/sup 2/. Inorganic phosphors exhibit reduced degradation with 90% of the degradation occurring within the first 2% of the material's lifetime. It is this stabilization that improves the viability of phosphor-coated CCD image sensors for commercial applications. The quantum efficiency observed was 12% at 265 nm. The improved deposition technique reduced the photoresponse nonuniformity degradation fourfold, so the observed PRNU was only 0.4 times greater than that of the uncoated sensor.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".