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Record W1996143017 · doi:10.1117/12.566966

Sub-spot-size CO 2 laser micromachining of features in fused silica by V-groove etching

2004· article· en· W1996143017 on OpenAlexaff
Alain Cournoyer, Luc Lévesque, Marc Lévesque

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsInstitut National d'Optique
Fundersnot available
KeywordsSurface micromachiningMaterials scienceGroove (engineering)Etching (microfabrication)OpticsLaserLaser ablationLaser beam machiningSubstrate (aquarium)MicrolensOptoelectronicsLaser beamsLens (geology)NanotechnologyLayer (electronics)Fabrication

Abstract

fetched live from OpenAlex

ABSTRACT Ablation of fused silica using the Gaussian irradiance profile of the TEM 00 mode of a CO 2 laser is a very efficient wayfor micromachining features up to ten times smaller than the beam diameter. A series of laser-etched V-groovessequentially shifted in a given fashion can be used to micromachine simple or structured patterns on the surface of fusedsilica substrates. Surface gratings with a periodicity of 12 µm were produced using a CO 2 laser beam of 100 µm (1/e 2 )in diameter. Rectangular wells 50 µm wide and 50 µm deep were also micromachined using the same technique with aradius of curvature of roughly 8 µm at the bottom edges. Although the resolution of the periodic pattern is not fullyunderstood, it appears to be partly governed by the amount of material removal by the top portion of the Gaussian beam(tip processing), as well as a carefully controlled shifting of the etched V-grooves on the fused silica substrate. Physicalmechanisms that could be at the origin of the V shape of the grooves are also discussed.Keywords: Laser ablation, laser micromachining, laser proce ssing, laser etching, fused silica, surface gratings

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 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 score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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 teacher head, not a consensus.

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

Citations1
Published2004
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicLaser Material Processing TechniquesFrench-language works237,207