Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 62 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 12 tok/s Pro
GPT-5 High 10 tok/s Pro
GPT-4o 91 tok/s Pro
Kimi K2 139 tok/s Pro
GPT OSS 120B 433 tok/s Pro
Claude Sonnet 4 31 tok/s Pro
2000 character limit reached

The Silicon Sensors for the High Granularity Calorimeter of CMS (2002.11449v3)

Published 26 Feb 2020 in physics.ins-det and hep-ex

Abstract: The installation of the High-Luminosity Large Hadron Collider (HL-LHC) presents unprecedented challenges to experiments like the Compact Muon Solenoid (CMS) in terms of event rate, integrated luminosity and therefore radiation exposures. To cope with this new environment, new detectors will be installed during the CMS Phase 2 Upgrade, including the replacement of the calorimeter endcaps with the "High Granularity Calorimeter" (HGCAL), which contains silicon sensors and scintillators as active elements. The silicon sensors will be produced in an 8" wafer process, which is new for high-energy physics, so it demands extensive quality verification. A first batch of prototype sensors underwent electrical tests at the institutes of the CMS Collaboration. Testing revealed major problems with the mechanical stability of the thin backside protective layer, that were not seen in earlier 6" prototypes produced by a different backside processing method. Following these results, the HGCAL group introduced the concept of "frontside biasing", allowing testing of the sensors without exposing its backside, verified the applicability, and adapted the prototype design to apply this method in series production.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (1)

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube