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Record W1985187993 · doi:10.1103/physrevb.70.184125

Spallation induced by ultrashort laser pulses at critical tension

2004· article· en· W1985187993 on OpenAlexaff
François Vidal, T. W. Johnston, J. C. Kieffer, F. Martín

Bibliographic record

VenuePhysical Review B · 2004
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsSpallationPhysicsSpinodal decompositionFluenceAtomic physicsTension (geology)Condensed matter physicsMaterials scienceLaserOpticsNuclear physicsThermodynamicsNeutronPhase (matter)Quantum mechanics

Abstract

fetched live from OpenAlex

Spallation, as induced by $50\phantom{\rule{0.3em}{0ex}}\mathrm{fs}$ laser pulses at the maximum possible tension (critical tension) in a $25\text{\penalty1000-\hskip0pt}\ensuremath{\mu}\mathrm{m}$ aluminum slab, was investigated by means of a one-dimensional fluid code. In the framework of our defect-free fluid model, spallation takes place through spinodal decomposition, a mechanism that differs from the usual mechanism of growth and coalescence of natural defects. Due to the slowing down of the hydrodynamic processes near critical tension, the spinodal decomposition time scale is about $1\phantom{\rule{0.3em}{0ex}}\mathrm{ns}$. Strain rates of about ${10}^{8}\phantom{\rule{0.3em}{0ex}}{\mathrm{s}}^{\ensuremath{-}1}$ and spall thicknesses of a few microns are obtained, in agreement with recent experiments using short laser pulses. The critical tension in the simulation $(12.8\phantom{\rule{0.3em}{0ex}}\mathrm{GPa})$ was somewhat larger than the tension inferred from experiments $(8.5\phantom{\rule{0.3em}{0ex}}\mathrm{GPa})$. Because of rapidly decreasing hydrodynamic coupling at higher laser fluences, the required laser spallation threshold fluence as predicted by the code $(410\phantom{\rule{0.3em}{0ex}}\mathrm{J}∕{\mathrm{cm}}^{2})$ is far higher than in experiments $(25\phantom{\rule{0.3em}{0ex}}\mathrm{J}∕{\mathrm{cm}}^{2})$. This large discrepancy in the spallation threshold fluence values might be due either to differences in the mechanisms through which spallation takes place, or to the specific choice of model for the equation of state.

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 categoriesInsufficient payload (model declined to judge)
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 score0.013
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.015
GPT teacher head0.288
Teacher spread0.273 · 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

Citations19
Published2004
Admission routes1
Has abstractyes

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