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Evaluation of 3D pixel silicon sensors for the CMS Phase-2 Inner Tracker
Institut für Hochenergiephysik, Wien, Austria. (CMS Collaboration)
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab. INFN Sezione di Padova, Padova, Italy. (CMS Collaboration)ORCID iD: 0000-0002-1659-8727
Vanderbilt University, Nashville, USA. (CMS Collaboration)
Number of Authors: 20002026 (English)In: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, ISSN 0168-9002, E-ISSN 1872-9576, Vol. 1088, article id 171359Article in journal (Refereed) Published
Abstract [en]

The high-luminosity upgrade of the CERN LHC requires the replacement of the CMS tracking detector to cope with the increased radiation fluence while maintaining its excellent performance. An extensive R&D program, aiming at using 3D pixel silicon sensors in the innermost barrel layer of the detector, has been carried out by CMS in collaboration with the FBK (Trento, Italy) and CNM (Barcelona, Spain) foundries. The sensors will feature a pixel cell size of 25 × 100μm2, with a centrally located electrode connected to the readout chip. The sensors are read out by the RD53A and CROCv1 chips, developed in 65 nm CMOS technology by the RD53 Collaboration, a joint effort between the ATLAS and CMS groups. This paper reports the results achieved in beam test experiments before and after irradiation, up to a fluence of approximately 2.6 × 1016 neq/cm2. Measurements of assemblies irradiated to a fluence of 1 x 1016 neq/cm2 show a hit detection efficiency higher than 96% at normal incidence, with fewer than 2% of channels masked, across a bias voltage range greater than 50 V. Even after irradiation to a higher fluence of 1.6 x  1016 neq/cm2, similar performance is maintained over a bias voltage range of 30 V, remaining well within CMS requirements.

Place, publisher, year, edition, pages
Elsevier BV , 2026. Vol. 1088, article id 171359
Keywords [en]
3D pixel, Silicon, Sensors, CMS experiment, High-Luminosity LHC, Radiation hardness
National Category
Subatomic Physics
Research subject
Machine Learning
Identifiers
URN: urn:nbn:se:ltu:diva-119453DOI: 10.1016/j.nima.2026.171359ISI: 001730180500001Scopus ID: 2-s2.0-105033336528OAI: oai:DiVA.org:ltu-119453DiVA, id: diva2:2093315
Note

For funding information, see: https://www.sciencedirect.com/science/article/pii/S0168900226000859?via%3Dihub#d1e6080;

Full text license: CC BY

Available from: 2026-08-18 Created: 2026-08-18 Last updated: 2026-08-21Bibliographically approved

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Dorigo, Tommaso

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