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Record W2753821179 · doi:10.1117/12.2283800

High frequency ultrasound generation by femtosecond laser ablation

2017· article· en· W2753821179 on OpenAlexaff
F. Blanchard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsLaserMaterials sciencePulse durationFemtosecondOpticsLaser ablationUltrasonic sensorAblationPenetration depthPlasmaAmplitudeUltrasoundAcousticsPhysics

Abstract

fetched live from OpenAlex

Laser ultrasonic measurements are emerging as an efficient means for remote probing of metals. This technique offers the possibility to perform non-contact measurements in a hostile environment, at high temperature, and on any kind of structure. There are two regimes for generating ultrasound in a metal: thermo-elastic and ablative. The former, uses low-energy laser pulses to heat the surface of the sample. The transient expansion of the near surface region launches compression waves into the sample. These displacements are very small (-10 pm) in metals because of the low optical penetration depth, such that lock-in detection techniques must be used for these measurements. In the ablative regime, a higher energy density laser pulse causes partial ablation of the target surface and ionisation of the ablated material. The plasma thus created can reach very high pressures, which causes the plasma to accelerate away from the surface and launches a compressive elastic wave into the sample. The amplitude of these waves is much greater (-10 nm) than those generated in the thermo-elastic regime and they can easily be measured by single shot interferometric techniques. Theoretical simulations of ablation by ultra-short laser pulses [F.Vidal et al., PRL, 86, 2573 (2001)] explore the generation of high frequency ultrasound waves (- GHz) in a thin aluminum film. These simulations indicate that the ultrasonic pulse duration is proportional to the laser pulse duration down to 100 ps, and that below 100 ps, further reduction of the laser pulse duration has little effect on the ultrasound pulse duration.

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 score0.037
Threshold uncertainty score0.577

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)0.0010.000

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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