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Record W1609761797 · doi:10.1063/1.1766734

Warpage Analysis of Silicon Wafer in Ingot Slicing by Wire-Saw Machine

2004· article· en· W1609761797 on OpenAlexaff
Toshiro Yamada

Bibliographic record

VenueAIP conference proceedings · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsCybernet Systems Corporation (Canada)
Fundersnot available
KeywordsSlicingIngotWaferImage warpingFinite element methodMaterials scienceSiliconMechanical engineeringEngineering drawingComputer scienceStructural engineeringEngineeringComposite materialMetallurgyOptoelectronics

Abstract

fetched live from OpenAlex

It is possible thermal expansion from heat generation by slicing deforms a single‐crystal silicon ingot but the authors can find no report on the point. In addition, numerical analysis is useful to clarify the mechanism of wafer warping but no paper has been reported the numerical analysis from the start to end of the wafer slicing process. The authors carried out experiments for the wafer slicing. In addition, a finite element analysis was carried out in order to solve the warping mechanism from the start to end of the wafer slicing process. The warp of wafer in the vertical direction was 6.05 μ m in the experiment whereas the warp in the finite element analysis was 5.30 μ m. The result by the finite element analysis gave good agreement with experimental one. This paper suggests that thermal expansion of the ingot has great influence on the warp of wafer.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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 designObservational
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

Citations11
Published2004
Admission routes1
Has abstractyes

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Same venueAIP conference proceedingsSame topicAdvanced Surface Polishing TechniquesFrench-language works237,207