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Sensors
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Novel Detectors for Particle Identification and Tracking
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Novel Detectors for Particle Identification and Tracking

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Materials".

Deadline for manuscript submissions: closed (10 November 2021) | Viewed by 6257

Special Issue Editors

Dr. Paolo Brogi

E-Mail Website
Guest Editor
University of Siena, Dept. of Physical Sciences, Earth and Environment (DSFTA) I-56100 Siena, Italyly
Interests: particle detectors; silicon detectors; SPADs; calorimetry; cosmic rays
Prof. Dr. Gabriele Bigongiari

E-Mail Website
Guest Editor
Dept. of Physical Sciences, Earth and Environment (DSFTA), University of Siena, I-56100 Siena, Italy
Interests: particle detectors; silicon detectors; SPADs; calorimetry; cosmic rays
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays particle detectors are employed in a variety of fields, and their application area is still spreading. It spans from fundamental research in particle physics to medical imaging, radiation monitoring, industrial applications, etc.

This has motivated an ever-increasing interest in innovative sensors for charged particle detection and identification with tracking capability. Each application has of course its own peculiarity, but an ideal novel detector is required to be highly granular, low power consuming, thin, fast, radiation tolerant, highly customizable and easy to read-out.

In this framework, I’m glad to edit this Special Issue on “Novel Detectors for Particle Identification and Tracking”.

The Special Issue is dedicated to presenting the most recent advances in the field of particle detection, introducing innovative technologies for charged particle identification and tracking.

Contributions describing new prototypes that exhibit remarkable improvements with respect to actual detectors or interesting concepts for developments of novel detectors are especially welcome.

Survey papers and reviews are also welcomed.

Dr. Paolo Brogi
Prof. Dr. Gabriele Bigongiari
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • particle detectors
  • novel detectors
  • particle identification
  • tracking
  • low power
  • low material budget
  • timing capability
  • radiation hardness
  • highly customizable detectors

Published Papers (2 papers)

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Research

21 pages, 4830 KiB  
Article
The SALT—Readout ASIC for Silicon Strip Sensors of Upstream Tracker in the Upgraded LHCb Experiment
by Carlos Abellan Beteta, Dimitra Andreou, Marina Artuso, Andy Beiter, Steven Blusk, Roma Bugiel, Szymon Bugiel, Antonio Carbone, Ina Carli, Bo Chen, Nadim Conti, Federico De Benedetti, Shuchong Ding, Scott Ely, Miroslaw Firlej, Tomasz Fiutowski, Paolo Gandini, Danielle Germann, Nathan Grieser, Marek Idzik, Xiaojie Jiang, Wojciech Krupa, Yiming Li, Zhuoming Li, Xixin Liang, Shuaiyi Liu, Yu Lu, Lauren Mackey, Jakub Moron, Ray Mountain, Marco Petruzzo, Hang Pham, Burkhard Schmidt, Shuqi Sheng, Elisabetta Spadaro Norella, Krzysztof Swientek, Tomasz Szumlak, Mark Tobin, Jianchun Wang, Michael Wilkinson, Hangyi Wu, Feihao Zhang and Quan Zouadd Show full author list remove Hide full author list
Sensors 2022, 22(1), 107; https://doi.org/10.3390/s22010107 - 24 Dec 2021
Cited by 4 | Viewed by 3375
Abstract
SALT, a new dedicated readout Application Specific Integrated Circuit (ASIC) for the Upstream Tracker, a new silicon detector in the Large Hadron Collider beauty (LHCb) experiment, has been designed and developed. It is a 128-channel chip using an innovative architecture comprising a low-power [...] Read more.
SALT, a new dedicated readout Application Specific Integrated Circuit (ASIC) for the Upstream Tracker, a new silicon detector in the Large Hadron Collider beauty (LHCb) experiment, has been designed and developed. It is a 128-channel chip using an innovative architecture comprising a low-power analogue front-end with fast pulse shaping and a 40 MSps 6-bit Analog-to-Digital Converter (ADC) in each channel, followed by a Digital Signal Processing (DSP) block performing pedestal and Mean Common Mode (MCM) subtraction and zero suppression. The prototypes of SALT were fabricated and tested, confirming the full chip functionality and fulfilling the specifications. A signal-to-noise ratio of about 20 is achieved for a silicon sensor with a 12 pF input capacitance. In this paper, the SALT architecture and measurements of the chip performance are presented. Full article
(This article belongs to the Special Issue Novel Detectors for Particle Identification and Tracking)
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12 pages, 1968 KiB  
Article
Simulation and Optimization Studies of the LHCb Beetle Readout ASIC and Machine Learning Approach for Pulse Shape Reconstruction
by Pawel Kopciewicz, Kazuyoshi Carvalho Akiba, Tomasz Szumlak, Sebastian Sitko, William Barter, Jan Buytaert, Lars Eklund, Karol Hennessy, Patrick Koppenburg, Thomas Latham, Maciej Majewski, Agnieszka Oblakowska-Mucha, Chris Parkes, Wenbin Qian, Jaap Velthuis and Mark Williams
Sensors 2021, 21(18), 6075; https://doi.org/10.3390/s21186075 - 10 Sep 2021
Cited by 2 | Viewed by 2204
Abstract
The optimization of the Beetle readout ASIC and the performance of the software for the signal processing based on machine learning methods are presented. The Beetle readout chip was developed for the LHCb (Large Hadron Collider beauty) tracking detectors and was used in [...] Read more.
The optimization of the Beetle readout ASIC and the performance of the software for the signal processing based on machine learning methods are presented. The Beetle readout chip was developed for the LHCb (Large Hadron Collider beauty) tracking detectors and was used in the VELO (Vertex Locator) during Run 1 and 2 of LHC data taking. The VELO, surrounding the LHC beam crossing region, was a leading part of the LHCb tracking system. The Beetle chip was used to read out the signal from silicon microstrips, integrating and amplifying it. The studies presented in this paper cover the optimization of its electronic configuration to achieve the lower power consumption footprint and the lower operational temperature of the sensors, while maintaining a good condition of the analogue response of the whole chip. The studies have shown that optimizing the operational temperature is possible and can be beneficial when the detector is highly irradiated. Even a single degree drop in silicon temperature can result in a significant reduction in the leakage current. Similar studies are being performed for the future silicon tracker, the Upstream Tracker (UT), which will start operating at LHC in 2021. It is expected that the inner part of the UT detector will suffer radiation damage similar to the most irradiated VELO sensors in Run 2. In the course of analysis we also developed a general approach for the pulse shape reconstruction using an ANN approach. This technique can be reused in case of any type of front-end readout chip. Full article
(This article belongs to the Special Issue Novel Detectors for Particle Identification and Tracking)
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