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Anomalous Ionization Regime in a Forced Electron Beam Induced Arc Discharge Ion Source for Singly Charged Radioactive Ion Beam Production

2022· article· en· W4224884254 on OpenAlexaff
Fernando Maldonado Millán, C. Babcock, T. Day Goodacre, A. Gottberg

Bibliographic record

VenueJournal of Physics Conference Series · 2022
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversity of VictoriaTRIUMF
Fundersnot available
KeywordsIon sourceIonizationAtomic physicsThermal emittanceIonElectron ionizationBeam (structure)ElectronArgonIon beamIon beam depositionChemistryNuclear physicsPhysicsOptics

Abstract

fetched live from OpenAlex

Abstract At TRIUMF’s ISAC facility, 1+ Radioactive Ion Beams (RIBs) of noble gases, halogens, and molecules are created using a Forced Electron Beam Induced Arc Discharge (FEBIAD) ion source. Reported ionization efficiencies for FEBIADs range from 10% to 25% for 40 Ar + , while TRIUMF-FEBIAD ionization efficiency seems to be < 1% with a 90% emittance <15 μm. As RIB ion sources aim for a high ionization efficiency, an experimental and numerical campaign was conducted to investigate the comparably low efficiencies observed. The experimental results for 40 Ar + indicate that up to a 10% ionization efficiency is possible by operating the source at different parameters. The measurements agree with theoretical estimations; however, certain combinations of parameters produce an anomalously high electron current which enhances the ionization efficiency threefold. Present investigations aim to characterize and model the anomalous electron current because, if proven reliable, the argon ionization efficiency could reach 30% with no significant impact on beam emittance.

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 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 score0.075
Threshold uncertainty score0.656

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)0.0000.000

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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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