Quantitative analysis of wide field-of-view and broadband quarter-wave plate based on metasurface
Bibliographic record
Abstract
As the numerical aperture (NA) of the projection objective increases continually and the exposure pattern feature size decreases gradually, the polarization illumination is introduced into the lithography system. Therefore, it is necessary to design a wide field-of-view (FOV) wave plate to eliminate the effect of oblique incident light on the phase delay of the traditional zero order wave plate effectively. The quarter-wave plate with 20° FOV based on birefringent optical crystals has been designed in our laboratory by Dong et al. In order to obtain a wider FOV, we explore a previously reported Ag patch ultrathin quarter-wave plate whose performances were not analyzed by finite-difference time-domain (FDTD) method. In this paper, we mainly investigate three performances of the Ag patch quarter-wave plate consisting of FOV, achromatic band and achromatic band transmission. The simulation results indicate that when phase difference error is controlled at ±2° (1) the range of FOV of the quarter-wave plate is ±29° at 632nm; (2) the achromatic band ranges from 618nm to 658nm at normal incidence; (3) the achromatic band transmission ranges from 11% to 30%. Compared with the traditional wave plate made of birefringent crystals, the achromatic band and transmission is slightly lower but the FOV of this quarter-wave plate is much wider. Thus, this Ag patch nanoscale wide FOV quarter-wave plate can be effectively used in high NA lithography projection exposure systems to reduce the polarization aberration caused by oblique incidence of light.
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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 | 0.001 | 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) | 0.001 | 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".