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Record W2057093311 · doi:10.1116/1.1924415

Imaging patterns of intensity in topographically directed photolithography

2005· article· en· W2057093311 on OpenAlexfundno aff
Kateri E. Paul, Tricia L. Breen, Tanja Hadzik, George M. Whitesides, Stephen P. Smith, Mara Prentiss

Bibliographic record

VenueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena · 2005
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsnot available
FundersMaterials Research Science and Engineering Center, Harvard UniversityNatural Sciences and Engineering Research Council of CanadaDefense Advanced Research Projects AgencyCalifornia Institute of TechnologyNational Science Foundation
KeywordsPhotoresistResistPhotolithographyIntensity (physics)OpticsLayer (electronics)Light intensityEmbossingLithographyMaterials scienceOptoelectronicsNanotechnologyPhysicsComposite material

Abstract

fetched live from OpenAlex

This article describes a process that consists of embossing a bas-relief pattern into the surface of a layer of photoresist and flood illuminating the embossed resist; this process uses the topography of the resist to generate a pattern of optical intensity inside the resist layer. Development of embossed, illuminated (λ=365–436nm) photoresist yields structures as small as 70nm. Numerical solutions of the Fresnel integral are used to calculate the pattern of intensity of light in the photoresist layer. Numeric simulation of a nondiffusion-limited development process results in theoretical structures that correlate well with the structures generated experimentally.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.006
GPT teacher head0.211
Teacher spread0.204 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and PhenomenaSame topicNanofabrication and Lithography TechniquesFrench-language works237,207