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Record W2163177753 · doi:10.1109/66.857943

Focus characterization using end of line metrology

2000· article· en· W2163177753 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIEEE Transactions on Semiconductor Manufacturing · 2000
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Photolithography Techniques
Canadian institutionsnot available
FundersOntario Council on Graduate Studies, Council of Ontario Universities
KeywordsMetrologyFocus (optics)OpticsOffset (computer science)Line (geometry)Lens (geology)Coordinate-measuring machinePhysicsRepeatabilityMathematicsComputer scienceGeometry

Abstract

fetched live from OpenAlex

A new method is introduced to measure relative focus using conventional optical overlay instruments. Optical end of line metrology (OELM), is based on patterning a wide frame in which adjacent sides are constructed of submicron sized lines that run perpendicular to the center opening. Because truncation is size dependent, line and space features exhibit significantly more line shortening effects than the solid sections. When measured with a conventional optical overlay tool, the difference in line shortening between the solid and line and space sections are measured as an alignment offset, which is a relative measure of actual line shortening. Reproducibility for measuring the apparent misalignment of these modified box-in-box structures was 3 nm (3/spl sigma//sup est/), which is similar to the repeatability for measuring conventional resist box in box alignment boxes. Truncation is sensitive to focus and the utility for using OELM toward characterizing focus-dependent lens parameters was investigated. Estimated 3/spl sigma/ for calculating best focus and astigmatism were 0.04 /spl mu/m and 0.01 /spl mu/m, respectively. Focus corrections were accurate to 0.05 /spl mu/m within /spl plusmn/0.3 /spl mu/m of best focus. Additionally, a general method is presented to estimate the error in the calculated best focus.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.292
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 head0.017
GPT teacher head0.244
Teacher spread0.227 · 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