Selection and evaluation of developer-soluble topcoat for 193nm immersion lithography
Bibliographic record
Abstract
Successful developer-soluble topcoats have to fulfill numerous requirements; specifically they have to serve as a barrier layer and be compatible with the resist. Some of the requirements and compatibility issues have been understood; others are still under-investigation by the joint efforts of lithographers and resist chemists. This paper addresses these requirements from the perspective of overall lithographic performance for developer-soluble topcoats used in 193nm water immersion lithography. We demonstrate that with the optimized combination of resist and developer-soluble topcoat 90nm 1:1 dense lines can be printed using a prototype tool, ASML AT 1150i, and a binary image mask (BIM) with a maximum depth-of-focus (DOF) of ~1.2μm. An approximate 2X DOF improvement over dry lithography that was theoretically expected has been truly demonstrated. Topcoat related defectivity as well as defect reduction efforts are also discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".