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Record W2148210649 · doi:10.1109/cleo.2000.907467

X-ray emission from femtosecond laser micromachining

2000· article· en· W2148210649 on OpenAlexaff
Jan Thøgersen, A. Borowiec, H. K. Haugen, Fiona E. McNeill, Ian Stronach

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials Research
Fundersnot available
KeywordsLaserSurface micromachiningFemtosecondMaterials scienceSapphireOpticsUltrashort pulseX-ray laserPulse durationOptoelectronicsTi:sapphire laserLaser beam machiningLaser power scalingPhysicsLaser beamsFabrication

Abstract

fetched live from OpenAlex

Summary form only given. Ultrafast lasers are rapidly becoming important tools in the micromachining and microprocessing of solids. Extremely short laser light pulses in the femtosecond regime lead to qualitatively different interactions with solids compared with light pulses of much longer duration. Pulse energies from high-repetition-rate solid state lasers deployed in femtosecond laser machining commonly range from /spl sim/0.1 /spl mu/J to /spl sim/1 mJ; with typical repetition rates in the 1-250 kHz regime. Focussing these light pulses to small spot sizes lead to very high peak intensities (/spl sim/10/sup 14/-10/sup 16/ W/cm/sup 2/), even for relatively compact (amplified) micromachining lasers. The characterization of hard photon emission, including in the X-ray region, is important for laser plasma characterization as well as in terms of workplace environmental considerations. Our investigations utilized an amplified Ti:sapphire laser system with pulses of 120 fs duration, up to 300 /spl mu/J in pulse energy, and operating at a 1 kHz repetition rate.

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 score0.071
Threshold uncertainty score0.990

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)0.0110.000

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 head0.006
GPT teacher head0.200
Teacher spread0.195 · 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

Citations2
Published2000
Admission routes1
Has abstractyes

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