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Upgrade and Improvement of the TRIUMF ECRIS Charge State Booster

2024· article· en· W4396919110 on OpenAlexaff
J Adegun, F. Ames, O. Kester

Bibliographic record

VenueJournal of Physics Conference Series · 2024
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsSaint Mary's UniversityUniversity of VictoriaTRIUMF
Fundersnot available
KeywordsBooster (rocketry)UpgradeNuclear physicsPhysicsState (computer science)Charge (physics)Nuclear engineeringEngineeringComputer scienceParticle physicsOperating systemProgramming languageAstronomy

Abstract

fetched live from OpenAlex

Abstract Recently, the RF system of the TRIUMF electron cyclotron resonance ion source charge state booster (ECRIS CSB) underwent an upgrade to implement two-frequency heating using a single waveguide. The injection and extraction optics, as well as the injection and extraction systems, were carefully modelled and systematically optimized to improve the efficiency and beam quality of the charge state booster. With optimized plasma and beam optics under the single-frequency heating regime, the maximum charge state of the 133 Cs isotope produced was 27+, with the peak of the charge state distribution at Cs 23+ with an efficiency of 8.5 %. However, with the implementation of two-frequency heating, the maximum charge state of Cs that can be produced increased to 32+, and the charge state distribution’s peak shifted to Cs 26+ with an efficiency of 9.1 %. Additionally, the two-frequency heating resulted in a total beam RMS emittance that was approximately half of the one that was measured under the single-frequency heating due to the more pronounced negative potential dip created at the plasma center.

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 score0.131
Threshold uncertainty score0.210

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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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