MétaCan
Menu
Back to cohort
Record W2145380776 · doi:10.1017/s1431927604040711

The Impact of Charging on Low-Energy Electron Beam Lithography

2004· article· en· W2145380776 on OpenAlexaff
Lau Kien Mun, Dominique Drouin, Éric Lavallée, Jacques Beauvais

Bibliographic record

VenueMicroscopy and Microanalysis · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Photolithography Techniques
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsElectron-beam lithographyLithographyExtreme ultraviolet lithographyMaterials scienceX-ray lithographyNext-generation lithographyVoltageResistMaskless lithographyAcceleration voltageOptoelectronicsCathode rayDistortion (music)OpticsElectronNanotechnologyCMOSPhysicsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

A major issue in low voltage lithography is surface charging, which results in beam deflection presented as uneven exposure between adjacent structures. In this study, charge-induced pattern distortions in low-voltage energy beam lithography (LVEBL) were investigated using a silicide direct-write electron beam lithography process. Two methodologies have been proposed to avert charging effects in LVEBL, namely, pattern randomizing and lithography using the crossover voltage. Experimental results demonstrated that these methods are effective in significantly reducing the problems associated with charging. They indicate that charging on a sample is a function of time interval and proximity between line structures. In addition, the optimum time and distance between exposures for no charge-induced pattern distortion were determined. By using the crossover voltage of the material for lithography, charging effect can be significantly minimized.

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)0.002
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
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.003
GPT teacher head0.252
Teacher spread0.249 · 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

Citations21
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueMicroscopy and MicroanalysisSame topicAdvancements in Photolithography TechniquesFrench-language works237,207