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Deep Junction LGAD: a new approach to high granularity LGAD

1 Dec 2022, 14:10
20m
Salón de Grados, 2nd Floor (ETSI Seville)

Salón de Grados, 2nd Floor

ETSI Seville

Escuela Técnica Superior de Ingenieros Camino de los Descubrimientos s/n 41092 Isla de la Cartuja, Sevilla Spain

Speaker

Simone Michele Mazza (University of California,Santa Cruz (US))

Description

Low Gain Avalanche Detectors (LGADs) are silicon detectors with modest internal gain (up to ~50) that allows the sensor to be very thin (20-50 um). LGADs are characterized by an extremely good time resolution (down to 17ps), a fast rise time (~500ps) and a very high repetition rate (~1ns full charge collection). In a broad array of fields, including particle physics (4-D tracking) and photon science (X-ray imaging), LGADs are a promising R&D path. However, due to structures required to provide electrostatic isolation between LGAD pixels, the granularity of production-level devices is limited to the 1x1 mm^2 scale. Applications in particle physics and photon science demand granularity scales of 100x100 um^2 or better. Several promising approaches to improve this current limitation of LGADs are currently in R&D status. In this talk, we'll present a recent new idea involving a buried gain layer to overcome the current granularity limit: the DJ-LGAD. The concept behind DJ-LGAD will be explained, then promising preliminary results from the first prototype production of DJ-LGADs will be shown.

Primary authors

Abraham Seiden (University of California,Santa Cruz (US)) Prof. Bruce Andrew Schumm (University of California,Santa Cruz (US)) Carolyn Gee (University of California,Santa Cruz (US)) Hartmut Sadrozinski (SCIPP, UC santa Cruz) Dr Jennifer Ott (University of California,Santa Cruz (US)) Simone Michele Mazza (University of California,Santa Cruz (US)) Yuzhan Zhao (University of California,Santa Cruz (US)) Yuzhan Zhao (University of California Santa Cruz)

Presentation materials