PixFEL - Enabling technologies, building blocks and architectures for advanced X-ray Pixel cameras at FELs


The goal of PixFEL project is to develop the technologies needed for the design of a large-area X-ray image sensor for applications at Free Electron Laser (FEL) facilities. Cutting-edge detector fabrication processes and innovative readout architectures are explored, and a prototype 32x32 pixelated hybrid detector will be produced at the end of the project.


The Science

The PixFEL project is conceived as the 1st stage of a long term research program aiming at the development of advanced X-ray imaging instrumentation for applications at the free electron laser (FEL) facilities. The project aims at substantially advance the state-of-the-art in the field of 2D X-ray imaging by furthering the understanding of FEL experiments requirements and exploration of cutting-edge solutions for fabrication technologies and detector readout architecture design.
For this purpose, the collaboration will develop the fundamental microelectronic building blocks for the front-end chip of an X-ray detector and will investigate the enabling technologies for the assembly of a multilayer four side buttable module, in particular active edge pixel sensors and low density, peripheral through silicon bias (TSV).
The PixFEL project will also study and implement a VHDL description of the readout architecture for the envisioned application. Design of the building blocks and of the readout architecture will be carried out in a 65 nm CMOS technology. As a final demonstrator, the project will produce a single tier 32x32 channel front-end chip interconnected to a fully depleted pixel sensor.

TEAM

• Involved external institutions: /
• INFN groups: Pavia, Pisa, TIFPA
• Principal Investigator: L. Ratti (INFN Pavia)
• INFN Project: CSN V
• Duration: 3 years (2014 - 2016)

TIFPA Team

• Local responsible for TIFPA: Lucio Pancheri
• Involved TIFPA people: Gian-Franco Dalla Betta, David Macii, Roberto Mendicino, Giovanni Verzellesi, Hesong Xu


      Images


 
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