You are here: Home Research ULTIMATE

ULTIMATE

Within the ERC-funded project ULTIMATE, we performed R&D towards the ultimate dark matter detector based on a dual-phase liquid xenon TPC. Such detector, possibly realized within the XLZD collaboration, will have a target mass of >40t of liquid xenon. Its sensitivity will start to be limited by coherent neutrino-nucleus interactions, a background which cannot be reduced by shielding.

The ULTIMATE team consisted of 1 professor, 2 PostDoc, 3 PhD students and several BSc and MSc students. We addressed the following questions:

  • How can we achieve the strict Rn-background requirements for DARWIN?
    →We studied an alternative detector design and work on improved material selection
  • How can we reduce the neutron background originating from PTFE?
    →The (not so) simple trick is to use less and cleaner PTFE.
  • Can we improve the design of the TPC to reduce these backgrounds?
    →We demonstrated a hermetically sealed TPC for this purpose .
  • Are there better alternatives to the dual-phase charge readout?
    → We operated the first TPC where the scintillation light is created in the liquid, which can solve some of the known problems.
  • Which (non-WIMP) science channels can be addressed by DARWIN?
    →We made detailed background studies to estimate DARWIN's sensitivity for WIMPs and studied neutrinoless double beta decay.
  • Which shields are required for DARWIN?
    →This is an important question to select the site of a real experiment. We performed simulations to address this.

 

Some of these projects were pursued in our laboratory in Freiburg. This unique building was re-furbished for our group recently and provides ideal conditions for large- and small-scale prototypes. It is equipped with a small class ISO-6 cleanroom.

Fotos: Oliver Kern (www.okdv.de), Architect: Roger Gerber
Please click on images to enlarge them.

 

The photo below shows one of our team members in the cleanroom, putting together a small-scale liquid xenon time projection chamber.

The project was funded by an ERC Consolidator Grant from the European Commission, project number 724320. erc.png