Thin n-in-p planar pixel modules for the ATLAS upgrade at HL-LHC

TL;DR

This paper investigates thin n-in-p planar pixel modules for the ATLAS upgrade at HL-LHC, focusing on their design, irradiation performance, and potential for improved tracking in high-radiation environments.

Contribution

It introduces new thin pixel sensor designs with optimized biasing and small pixel sizes, assessing their efficiency and charge collection after irradiation.

Findings

High hit efficiency maintained after irradiation

Effective charge collection in thin sensors

Feasibility of small pixel sizes for high-luminosity tracking

Abstract

The ATLAS experiment will undergo a major upgrade of the tracker system in view of the high luminosity phase of the LHC (HL-LHC) foreseen to start around 2025. Thin planar pixel modules are promising candidates to instrument the new pixel system, thanks to the reduced contribution to the material budget and their high charge collection efficiency after irradiation. New designs of the pixel cells, with an optimized biasing structure, have been implemented in n-in-p planar pixel productions with sensor thicknesses of 270 um. Using beam tests, the gain in hit efficiency is investigated as a function of the received irradiation fluence. The outlook for future thin planar pixel sensor productions will be discussed, with a focus on thin sensors with a thickness of 100 and 150 um and a novel design with the optimized biasing structure and small pixel cells (50 um x 50 um and 25 um x 100 um). These dimensions are foreseen for the new ATLAS read-out chip in 65 nm CMOS technology and the fine segmentation will represent a challenge for the tracking in the forward region of the pixel system at HL-LHC. To predict the performance of 50 um x 50 um pixels at high eta, FE-I4 compatible planar pixel sensors have been studied before and after irradiation in beam tests at high incidence angle with respect to the short pixel direction. Results on cluster shapes, charge collection- and hit efficiency will be shown.