Curing early breakdown in silicon strip sensors with radiation
Bibliographic record
Abstract
In preparation for the forthcoming High-Luminosity phase of the Large Hadron Collider, the ATLAS experiment is working on major upgrades to its detector systems to effectively accommodate the increase in radiation levels and track density. The foremost among these upgrades entails the replacement of the current inner tracking detector with an advanced all-silicon Inner Tracker (ITk). In the outer region of the ITk apparatus is the Strip Detector. Central to the new strip tracking system are the ITk Strip modules, comprising silicon sensors and hybrid Printed Circuit Boards housing the integral read-out Application-Specific Integrated Circuits (ASICs) as well as power distribution services. Thorough characterisation of the electrical characteristics of the silicon strip modules at various stages of the assembly procedure holds paramount significance in evaluating module performance. This rigorous evaluation ensures timely identification of any anomalies, thereby enabling proactive remedial measures. Notably, during the course of these electrical assessments, certain modules manifested breakdown phenomena occurring below the prescribed threshold of 500 V, mandated by the ITk Quality Control protocols. Based on these observations, controlled exposure to low levels of radiation was suspected to elevate the breakdown voltage in susceptible sensors. This contribution presents results from two irradiation campaigns to investigate potentially beneficial effects of irradiation. One study investigates the effects of gamma irradiation on modules showing an early breakdown after gluing. For this study, modules were exposed to an ionising dose of 11 krad (corresponding to the dose accumulated after several days of operation in the HL-LHC) utilising a 60Co source. The second campaign focuses on silicon sensor test structures with low breakdown voltage due to intentionally caused mechanical defects and their development after exposure to reactor neutrons. In both cases, preliminary findings suggest a discernible improvement in the breakdown voltage.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".