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Record W4401798120 · doi:10.1088/1402-4896/ad7352

Multilayer film coating for laser ion source target for increase of low charge state production

2024· article· en· W4401798120 on OpenAlex
Giovanni Ceccio, Shunsuke Ikeda, Takeshi Kanesue, Antonino Cannavò, M. Cutroneo, Pavel Pleskunov, Kazumasa Takahashi, M. Okamura

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysica Scripta · 2024
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsPolytechnique Montréal
FundersU.S. Department of Energy
KeywordsMaterials scienceCoatingCharge (physics)LaserIonProduction (economics)OptoelectronicsAtomic physicsEngineering physicsNanotechnologyOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract The use of Laser Ion Source for accelerator facilities has the advantage to tune the characteristic of the produced beams by changing the laser parameters using the same primary target. The advantageous and innovative opportunity to manipulate the characteristic of charge state distributions by the use of composed target, may open new possibilities for the ion sources. In this experiment we characterize and study the plasma produced by the laser ablation of coated targets at constant laser parameters. The performed investigation has the double purpose to have a better understanding of penetration depth of laser in composed materials and understand how to tune the charge states by adding coating films. The obtained results showed that for particular thickness of coating, the low charge states were produced with higher yield than in the case of pure material.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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