Published March 2025 | Published
Journal Article

Results for pixel and strip centimeter-scale AC-LGAD sensors with a 120 GeV proton beam

  • 1. ROR icon Fermilab
  • 2. ROR icon Lawrence Berkeley National Laboratory
  • 3. ROR icon University of Illinois at Chicago
  • 4. ROR icon Federico Santa María Technical University
  • 5. Millennium Institute for Subatomic Physics at the High-Energy Frontier (SAPHIR) of ANID, Fernández Concha 700, Santiago, Chile
  • 6. ROR icon Brookhaven National Laboratory
  • 7. ROR icon Alikhanyan National Laboratory
  • 8. ROR icon Kyungpook National University
  • 9. ROR icon University of Iowa
  • 10. ROR icon High Energy Accelerator Research Organization
  • 11. ROR icon University of Tsukuba
  • 12. ROR icon California Institute of Technology

Abstract

We present the results of an extensive evaluation of strip and pixel AC-LGAD sensors tested with a 120GeV proton beam, focusing on the influence of design parameters on the sensor temporal and spatial resolutions. Results show that reducing the thickness of pixel sensors significantly enhances their time resolution, with 20-μm-thick sensors achieving around 20ps. Uniform performance is attainable with optimized n⁺ sheet resistance, making these sensors ideal for future timing detectors. Conversely, 20-μm-thick strip sensors exhibit higher jitter than similar pixel sensors, negatively impacting time resolution, despite reduced Landau fluctuations with respect to the 50- μm-thick versions. Additionally, it is observed that a low resistivity in strip sensors limits signal size and time resolution, whereas higher resistivity improves performance. This study highlights the importance of tuning the n⁺ sheet resistance and suggests that further improvements should target specific applications like the Electron-Ion Collider or other future collider experiments. In addition, the detailed performance of four AC-LGADs sensor designs is reported as examples of possible candidates for specific detector applications. These advancements position AC-LGADs as promising candidates for future 4D tracking systems, pending the development of specialized readout electronics.

Copyright and License

© 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Acknowledgement

We thank the Fermilab accelerator and FTBF personnel for the excellent performance of the accelerator and support of the test beam facility, in particular M. Kiburg, E. Niner, N. Pastika, E. Schmidt and T. Nebel. We also thank the SiDet department, in particular M. Jonas and H. Gonzalez, for preparing the readout board by mounting and wirebonding the LGAD sensors. Finally, we thank L. Uplegger for developing and maintaining the telescope tracking system.

This document was prepared using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. This work was also supported by the U.S. Department of Energy (DOE), Office of Science, Office of High Energy Physics Early Career Research program award. This work was also supported by funding from University of Illinois Chicago under Contract DE-FG02-94ER40865 with the U.S. Department of Energy (DOE), and Contract 418643 with Brookhaven National Laboratory. This work has also been supported by funding from the California Institute of Technology High Energy Physics under Contract DE-SC0011925 with the U.S. Department of Energy. This work was supported by the Science Committee of Republic of Armenia (Research projects No. 22AA-1C009 and 22rl-037). This work was supported by the Chilean ANID PIA/APOYO AFB230003 and ANID - Millennium Science Foundation - ICN2019_044.

Contributions

Irene Dutta: Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation, Formal analysis, Data curation. Christopher Madrid: Conceptualization, Data curation, Investigation, Methodology, Software, Supervision, Validation, Writing – review & editing. Ryan Heller: Conceptualization, Data curation, Methodology, Software, Supervision, Writing – review & editing. Shirsendu Nanda: Data curation, Formal analysis, Investigation, Software, Writing – original draft. Danush Shekar: Data curation, Formal analysis, Investigation, Software, Validation, Writing – original draft. Claudio San Martín: Formal analysis, Software. Matías Barría: Formal analysis, Software. Artur Apresyan: Funding acquisition, Resources, Writing – review & editing. Zhenyu Ye: Data curation, Funding acquisition, Project administration, Resources, Writing – review & editing. William K. Brooks: Funding acquisition, Resources. Wei Chen: Resources. Gabriele D’Amen: Data curation, Writing – review & editing. Gabriele Giacomini: Funding acquisition, Resources, Writing – original draft, Writing – review & editing. Alessandro Tricoli: Funding acquisition, Resources, Writing – review & editing. Aram Hayrapetyan: Data curation, Formal analysis. Hakseong Lee: Data curation. Ohannes Kamer Köseyan: Data curation. Sergey Los: Resources. Koji Nakamura: Funding acquisition, Resources, Writing – review & editing. Sayuka Kita: Resources. Tomoka Imamura: Resources. Cristián Peña: Funding acquisition. Si Xie: Funding acquisition.

Data Availability

Data will be made available on request.

Additional details

Created:
January 29, 2025
Modified:
January 29, 2025