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A 0.3nV/√Hz input-referred-noise analog front-end for radiation-induced thermo-acoustic pulses

Authors :
Andrea Baschirotto
R. Bertoni
Marcello De Matteis
Elia Arturo Vallicelli
Luca Gelmi
Alessandro Quintino
Massimo Corcione
A. Baù
W. Fulgione
Davide Turossi
Vallicelli, E
Turossi, D
Gelmi, L
Bau, A
Bertoni, R
Fulgione, W
Quintino, A
Corcione, M
Baschirotto, A
De Matteis, M
Source :
Integration. 74:11-18
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

This paper presents the design and the experimental characterization of a complete acoustic analog front-end (A-AFE) read-out channel for detecting thermo-acoustic pulses induced by heavy-charged particles interacting with matter. The most relevant applications are in particle physics experiments (bubble chambers for Dark Matter Weakly Interacting Massive Particles (WIMPs) detection) and biomedical (beam range verification in oncological hadron-therapy). Typical thermo-acoustic pulses are characterized by 50 kHz–500 kHz bandwidth and weak amplitudes (around 5–50 Pa) and thus require low-noise piezoelectric-based ultrasound sensors (with input-referred noise power spectral density, IRN-PSD, as low as 1–2 nV/√Hz) whose output signal is 1–10 μV0-PEAK amplitude. Thus, even lower noise electronics are needed to preserve the weakest signal and maximize the sensitivity of the whole detector. For this reason, the A-AFE has been designed to achieve a global 0.3 dB Noise Figure with an input-referred detector noise floor as low as 2.3 μVRMS (corresponding to 93 mPaRMS) thanks to a dedicated JFET-based low-noise amplifier. The A-AFE achieves 31.5 dB Signal-to-Noise-Ratio at 4.8 Pa and 160 kHz pressure source. The final A-AFE prototype has 45 dB in-band gain at 0.3 nV/√Hz Input Referred Noise and it is the first specifically designed and optimized for sensing the acoustic signal coming from interactions between radiations and matter.

Details

ISSN :
01679260
Volume :
74
Database :
OpenAIRE
Journal :
Integration
Accession number :
edsair.doi.dedup.....f3f2736e03f107365b935c68c5ef29f8