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Record W1975548459 · doi:10.1117/12.567746

Surface modifications during femtosecond laser ablation in vacuum, air, and water

2004· article· en· W1975548459 on OpenAlexaff
Sébastien Besner, Jean-Yves Degorce, Andrei V. Kabashin, Michel Meunier

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceAblationLaser ablationLaserFemtosecondIrradiationAbsorption (acoustics)Impact craterPlasmaRadiationOpticsFluenceAnalytical Chemistry (journal)Atomic physicsPhysicsComposite materialChemistry

Abstract

fetched live from OpenAlex

Femtosecond laser ablation technique has been used to process Si and Au targets in vacuum, air and water environment. The threshold of ablation was found to be much lower for Si compared to Au and that was related to much better radiation absorption of Si. The values of the threshold were almost identical for vacuum, air and water in the case of Si (0.4 J/cm<sup>2</sup> 0.2 J/cm<sup>2</sup> in the single and multi-pulse irradiation regime, respectively) and Au (0.9 J/cm<sup>2</sup> and 0.3 J/cm<sup>2</sup>). Craters on the surface of Si and Au were essentially similar for low fluences, suggesting an involvement of the same radiation-related mechanism of material removal, whereas for high fluences significant differences could take place. In particular, quite different crater morphologies were observed during the laser ablation in water, including ones with nanoporous layers for Si and ones with concentric spheres for Au. The differences of morphologies for high laser fluences were explained by the involvement of plasma-related effects under the processing in relatively dense media.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.067
Threshold uncertainty score0.950

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 communication0.0000.001
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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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.

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

Citations12
Published2004
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicLaser-induced spectroscopy and plasmaFrench-language works237,207