MétaCan
Menu
Back to cohort
Record W1980347354 · doi:10.1117/12.655725

Selection and evaluation of developer-soluble topcoat for 193nm immersion lithography

2006· article· en· W1980347354 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Photolithography Techniques
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsImmersion lithographySelection (genetic algorithm)LithographyImmersion (mathematics)Computer scienceResistMaterials scienceMathematicsArtificial intelligenceNanotechnologyOptoelectronicsGeometry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.248
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it