Feb 17 – 21, 2025
Vienna University of Technology
Europe/Vienna timezone

ASTRA-64 : Tests and Characterization of a Silicon Micro-Strip Detectors Read-Out ASIC

Feb 18, 2025, 3:40 PM
50m
Vienna University of Technology

Vienna University of Technology

Gusshausstraße 27-29, 1040 Wien
Board: 19
Poster Electronics Coffee & Posters A

Speaker

Gianluigi Silvestre (Universita e INFN, Perugia (IT))

Description

Silicon strip detectors remain a popular choice in various fields of physics due to their flexibility and capability to achieve high spatial resolutions, ranging from tens of micrometers to less than 5 micrometers while covering large areas up to several square meters. The ASTRA-64 (Adaptable Silicon sTrip Read-out ASIC) is a 64-channel mixed-signal ASIC designed to read micro-strip silicon detectors. Designed in 110 nm technology, ASTRA-64 consists of two mirrored blocks of 32 channels. Each channel is equipped with a Charge-Sensitive Amplifier featuring two programmable gain settings for both input signal polarities, followed by a shaper with programmable peaking time to optimize noise performance based on the detector's capacitance.

ASTRA-64 supports two read-out modes: an analog mode, where charge information is transmitted off-chip via an analog multiplexer, and a digital mode, which embeds a Wilkinson ADC per channel for voltage digitization. The front-end gain configuration allows linear charge measurements up to 160 fC in standard gain and 80 fC in high gain mode. Finally, a fast shaper coupled with a leading-edge hysteresis discriminator enables rapid trigger signal generation through FAST-OR logic from the 32-channel discriminator outputs.

This work presents the testing, characterization, and performance evaluation of the ASTRA-64 chip.

Authors

Angelo Rivetti (Universita e INFN Torino (IT)) Fabio Cossio (INFN Torino (IT)) Gianluigi Silvestre (Universita e INFN, Perugia (IT))

Co-authors

Giovanni Ambrosi (Universita e INFN, Perugia (IT)) Manuel Dionisio Da Rocha Rolo Maria Movileanu (Universita e INFN, Perugia (IT)) Matteo Duranti (Universita e INFN, Perugia (IT)) Mattia Barbanera (Universita e INFN, Perugia (IT)) Pisana Placidi (Universita e INFN, Perugia (IT)) Raffaele Aaron Giampaolo (Université de Sherbrooke)

Presentation materials