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arXiv · 1806.06040

Materials Informatics for Dark Matter Detection

R. Matthias Geilhufe·Bart Olsthoorn·Alfredo Ferella·Timo Koski·Felix Kahlhoefer·Jan Conrad·Alexander V. Balatsky
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Abstract

Dark Matter particles are commonly assumed to be weakly interacting massive particles (WIMPs) with a mass in the GeV to TeV range. However, recent interest has shifted towards lighter WIMPs, which are more difficult to probe experimentally. A detection of sub-GeV WIMPs would require the use of small gap materials in sensors. Using recent estimates of the WIMP mass, we identify the relevant target space towards small gap materials (100-10 meV). Dirac Materials, a class of small- or zero-gap materials, emerge as natural candidates for sensors for Dark Matter detection. We propose the use of informatics tools to rapidly assay materials band structures to search for small gap semiconductors and semimetals, rather than focusing on a few preselected compounds. As a specific example of the proposed strategy, we use the organic materials database (omdb.diracmaterials.org) to identify organic candidates for sensors: the narrow band gap semiconductors BNQ-TTF and DEBTTT with gaps of 40 and 38 meV, and the Dirac-line semimetal (BEDT-TTF)$\cdot$Br which exhibits a tiny gap of $\approx$ 50 meV when spin-orbit coupling is included. We outline a novel and powerful approach to search for dark matter detection sensor materials by means of a rapid assay of materials using informatics tools.

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R. Matthias Geilhufe, Bart Olsthoorn, Alfredo Ferella, Timo Koski, Felix Kahlhoefer, Jan Conrad, Alexander V. Balatsky. 2018-06-15. Materials Informatics for Dark Matter Detection. https://doi.org/10.1002/pssr.201800293

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