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

Characterisation of analogue MAPS fabricated in 65 nm technology for the ALICE ITS3 (2409.07543v1)

Published 11 Sep 2024 in physics.ins-det and hep-ex

Abstract: The ALICE ITS3 project foresees the use of ultra-light MAPS, developed in the 65 nm imaging process, for the vertex detector in the ALICE experiment at the LHC to drastically improve the vertexing performance. This new development, initiated by an international consortium of the ALICE ITS3 collaboration and the CERN EP R&D project, enhances the overall MAPS performance. Small-scale prototypes are designed to study the analogue properties of the TPSCo 65 nm technology and compare the charge collection performance in different processes, pitches, pixel geometries, and irradiation levels. Recent results from lab and test-beam characterisation detailing the efficiency and the spatial resolution of the APTS with different pixel geometries and pitches satisfy the ALICE ITS3 requirements. A quantitative evolution of the charge collection and sharing among pixels is evident in the CE-65 with different in-pixel readouts. Attaining a spatial resolution better than 3 $\mu$m with a 10 $\mu$m pitch and over 99% efficiency in the moderate irradiation environment of ALICE also supports the viability of using 65 nm MAPS for FCC-ee vertex detectors.

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 (2)

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