Expanding grayscale capability of direct-write grayscale photomask by using modified Bi/In compositions
Bibliographic record
Abstract
Bimetallic thin films have been proven to be effective in creating analog direct write grayscale photomasks. DC-sputtered Bi/In or Sn/In oxidizes under laser writing exposure. The optical density decreases from >3OD as deposited to a transparency of <0.22OD at 365 nm with increasing laser power. The bimetallic film has a response curve that is nearly linear for much of the curve, but non-linear at maximum absorption and transmission. In order to create more accurate gray levels, a more gradual OD change versus laser writing power is desired. In this research a new reactive sputtered, oxygenated Bi/In film was created that has an 8-bits grayscale level sensitivity of 1.1 gray levels/mV, compared with the previous Bi/In of 3.2 gray levels/mV and Sn/In of 2.8 gray levels/mV. This modified Bi/In film provides more than twice the laser writing power range for controlling the same OD range, as compared to our original Bi/In or Sn/In films. This wider power range provides easier and more accurate laser power-to-grayscale calibration, because each grayscale can now be spaced more evenly over the increased laser writing power range. In addition, the surface of modified Bi/In is found to be much smoother than the original Bi/In and Sn/In films, thus increasing the overall quality of grayscale photomask. Finally grayscale uniformity of the laser writing process has been investigated and techniques such as laser beam shaping and defocusing have been used successfully to eliminate the variations.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".