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Record W4396786051 · doi:10.1016/j.nima.2024.169430

Long-term humidity exposure of ATLAS18 ITk strip sensors

2024· article· en· W4396786051 on OpenAlexafffund
V. Fadeyev, A. A. Affolder, A. Dowling, J. Fernández-Tejero, J. Gunnell, Nan Kang, F. Martinez-Mckinney, Q. Paddock, M. Ullán, Y. Unno, J. Yarwick

Bibliographic record

VenueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsSimon Fraser UniversityTRIUMF
FundersConsejo Superior de Investigaciones CientíficasNatural Sciences and Engineering Research Council of CanadaCERNCanada Foundation for InnovationU.S. Department of Energy
KeywordsTerm (time)HumidityEnvironmental scienceMeteorologyPhysicsAstronomy

Abstract

fetched live from OpenAlex

The ATLAS collaboration is upgrading its detector for High-Luminosity LHC (HL-LHC) operations scheduled to start in 2029. This involves making a new all-silicon tracker, called Inner Tracker (ITk), with instrumented strip area of 165 m 2 . The strip sensor type is n-on-p, chosen because of its radiation hardness and a relative fabrication simplicity. So far, this technology has not been used in large-scale experiments. Many years of R&D investigations and pre-production experience showed that it works well, with the specification of the maximum operational voltage of 500 V. The sensors, however, show sensitivity to ambient humidity, e.g. reduced breakdown voltage at relative humidity (RH) values of about 40% and above. This is an issue for testability , but not for real operations, where RH is very low. Therefore, the collaboration adopted the strategy of dry storage, testing, and shipment for sensors and related assembled components: modules, staves, and petals. A few days long exposure to ambient air during assembly was shown to be tolerable. The dry handling strategy becomes much more difficult to implement during the tracker integration, when barrels and disks are put together in large-size cleanrooms with RH range between 50 and 70%. The duration of each of numerous integration steps is several weeks, followed by testing. The effect of such long humidity exposures on the sensor properties was unknown. Therefore, we commenced a study of repeated sensor exposures to 75% RH. We chose 32 sensors for the study from different deliveries, and with different pedigrees in terms of initial performance on reception and recovery procedures used. Progressively longer exposures ranged between 4 and 266 days in duration. The cumulative exposure time was up to 2 years. No performance deterioration was seen, as evaluated by the visual inspection, IV characteristics, and other checks. We report the details of the tests, results, and implications. • Silicon sensors do not change performance after up to 2.6 years of humidity exposure. • Some of the sensors have been recovered on reception, but they also performed well. • We have seen no sign of corrosion. • Breakdown voltage depends on humidity, but performance in dry environment is good.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.385
Teacher spread0.328 · 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 designObservational
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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

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