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Record W4400913898 · doi:10.1016/j.nima.2024.169621

TCAD simulation of the electrical performance of the ATLAS18 strip sensor for the HL-LHC

2024· article· en· W4400913898 on OpenAlexaff
C. E. Jessiman, J. R. Dandoy, V. Fadeyev, Robert Griffin, J. Keller, C. Klein, T. Koffas, E. J. Staats, M. Ullán, Y. Unno, A. Walker

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 institutionsNational Research Council CanadaCarleton University
Fundersnot available
KeywordsLarge Hadron ColliderMaterials scienceComputer scienceOptoelectronicsElectrical engineeringPhysicsEngineeringParticle physics

Abstract

fetched live from OpenAlex

To cope with the increased occupancy and radiation dose expected at the High-Luminosity LHC , the ATLAS experiment will replace its current Inner Detector with the Inner Tracker (ITk), consisting of silicon-based pixel and strip sub-detectors. The strip detector will consist of n + -in- p sensors fabricated by Hamamatsu Photonics , with 300 μ m signal-generation thickness and approximately 75 μ m strip pitch. To guide the operation of these sensors in the ITk, it is desirable to understand the basic mechanisms underlying their performance, including the effects of the radiation fluence (up to 1 . 6 × 1 0 15 1-MeV n eq /cm 2 ) expected during operation. To this end, we have used Sentaurus TCAD to develop a 2D simulation of the ITk large-format strip sensor, based on detailed optical and electrical measurements of the sensors and of test devices fabricated on the same wafers. Current–voltage and capacitance–voltage behaviour is reproduced in the simulation by implementing charge trapping due to defects in the silicon , and the dependence of sensor behaviour on the location of these defects is investigated. Defect parameters are obtained using existing frameworks, such as the Perugia model of surface and bulk radiation damage, and through deep-level transient spectroscopy of test devices on the sensor wafers.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.054
GPT teacher head0.379
Teacher spread0.325 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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