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Record W2061078683 · doi:10.1117/12.826646

K-alpha x-ray source using high energy and high repetition rate laser system for phase contrast imaging

2009· article· en· W2061078683 on OpenAlexafffund
Cristina Şerbănescu, S. Fourmaux, Jean-Claude Kieffer, Russell Kincaid, Andrzej Król

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Institute of Biomedical Imaging and BioengineeringNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsOpticsLaserContrast (vision)Alpha (finance)Energy (signal processing)X-Ray Phase-Contrast ImagingPhase-contrast imagingPhase (matter)Repetition (rhetorical device)High contrastMaterials sciencePhase contrast microscopyX-rayPhysicsMathematics

Abstract

fetched live from OpenAlex

K-alpha x-ray sources from laser produced plasmas provide completely new possibilities for x-ray phase-contrast imaging applications. By tightly focusing intense femtosecond laser pulses onto a solid target K-alpha x-ray pulses are generated through the interaction of energetic electrons created in the plasma with the bulk target. In this paper, we present a continuous and efficient Mo K-alpha x-ray source produced by a femtosecond laser system operating at 100 Hz repetition rate with maximum pulse energy of 110 mJ before compression. The source has an x-ray conversion efficiency of greater than 10(-5) into K-alpha line emission. In preparation for phase contrast imaging applications, the size of the resultant K-alpha x-ray emission spot has been also characterized. The source exhibits sufficient spatial coherence to observe phase contrast. We observe a relatively small broadening of the K-alpha source size compared to the size of the laser beam itself. Detailed characterization of the source including the x-ray spectrum and the x-ray average yield along with phase contrast images of test objects will be presented.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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

Citations8
Published2009
Admission routes2
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced X-ray Imaging TechniquesFrench-language works237,207