TCAD simulation of the electrical performance of the ATLAS18 strip sensor for the HL-LHC
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".