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Record W2577572121 · doi:10.1117/12.697293

Femtosecond interaction processes near threshold: damage and ablation

2006· article· en· W2577572121 on OpenAlexaff
R. Fedosejevs, Sean E. Kirkwood, Roman Holenstein, N. Young, Ying Y. Tsui

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicroelectronicsFemtosecondMaterials scienceImpact ionizationSemiconductorSiliconSurface micromachiningIonizationOptoelectronicsLaser ablationLaserAblationThermal conductivityNanotechnologyFabricationOpticsChemistryPhysicsIonComposite material

Abstract

fetched live from OpenAlex

Femtosecond laser ablation is an important process in micromachining and nanomachining of microelectronic, optoelectronic, biophotonic and MEMS components. It is also important in the damage of optical components and materials. A thorough understanding of all aspects of femtosecond matter interaction processes in the near-threshold regime is required if one wants to have complete control of these processes. Two aspects of the interaction process for metals and semiconductors are examined in detail in the present paper, namely the effect of a more complete model for the temperature dependent electron thermal conductivity in metals and the avalanche ionization process in semiconductors. These are included in two temperature and molecular dynamics modeling calculations respectively. The proper inclusion of these processes allows the model calculations to better reproduce published experimental measurements for copper and silicon.

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.223
Teacher spread0.214 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicLaser Material Processing TechniquesFrench-language works237,207