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Record W2072527284 · doi:10.1063/1.1944223

High-resolution study of photoinduced modification in fused silica produced by a tightly focused femtosecond laser beam in the presence of aberrations

2005· article· en· W2072527284 on OpenAlexaff
Cyril Hnatovsky, R. S. Taylor, E. Simova, V. R. Bhardwaj, D. M. Rayner, P. B. Corkum

Bibliographic record

VenueJournal of Applied Physics · 2005
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsSteacie Institute for Molecular SciencesInstitute for Microstructural Sciences
Fundersnot available
KeywordsFemtosecondOpticsSpherical aberrationMaterials scienceNumerical apertureLaserLens (geology)Etching (microfabrication)Refractive indexIrradiationResolution (logic)Isotropic etchingAperture (computer memory)OptoelectronicsNanotechnologyPhysics

Abstract

fetched live from OpenAlex

An ultrahigh-resolution (20nm) technique of selective chemical etching and atomic force microscopy has been used to study the photoinduced modification in fused silica produced at various depths by tightly focused femtosecond laser radiation affected by spherical aberration. We demonstrate that shapes of the irradiated zones near the threshold for modification can be predicted by taking proper account of spherical aberration caused by the refractive index mismatched air–silica interface. We establish a depth dependence of the pulse energy required to initiate modification and characterize the relationship between numerical aperture of the writing lens and practically achievable writing depth. We also show that spatial characteristics of the laser-modified zones can be controlled by a specially designed focusing system which allows correction for a variable amount of spherical aberration.

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 score0.002
Threshold uncertainty score0.003

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)0.0000.000

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 head0.018
GPT teacher head0.240
Teacher spread0.222 · 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

Citations117
Published2005
Admission routes1
Has abstractyes

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