MétaCan
Menu
Back to cohort
Record W2073821509 · doi:10.1103/physrevb.67.184102

Molecular-dynamics study of ablation of solids under femtosecond laser pulses

2003· article· en· W2073821509 on OpenAlexaff
Danny Pérez, Laurent J. Lewis

Bibliographic record

VenuePhysical review. B, Condensed matter · 2003
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsFluenceFemtosecondMaterials scienceSpallationLaserAblationPlasmaAtomic physicsLaser ablationRelaxation (psychology)VaporizationMolecular dynamicsMolecular physicsOpticsPhysicsThermodynamicsNeutronNuclear physics

Abstract

fetched live from OpenAlex

The ablation of solids under femtosecond laser pulses is studied using a two-dimensional molecular-dynamics model. The simulations show that different expansion regimes develop as a function of the injected energy. The origin of these regimes lies in changes of the thermodynamical relaxation path the material follows when the intensity of the laser increases. The shape of the pressure waves generated as a result of the absorption of the pulse is shown to vary from bipolar at low fluence to unipolar at high fluence, as a result of the decrease of the tensile strength of the material with temperature. By combining these results with an analysis of the thermodynamical trajectories for different portions of the target, we show that four different mechanisms can account for ablation at fluences below the threshold for plasma formation, namely spallation, phase explosion, fragmentation, and vaporization. These mechanisms are characterized in detail; it is demonstrated that they can occur simultaneously in different parts of the target.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.282
Teacher spread0.271 · 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 designSimulation or modeling
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

Citations320
Published2003
Admission routes1
Has abstractyes

Explore more

Same venuePhysical review. B, Condensed matterSame topicLaser Material Processing TechniquesFrench-language works237,207