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Materials Informatics for Dark Matter Detection
KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Stockholm Univ, Roslagstullsbacken 23, SE-10691 Stockholm, Sweden..
KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Stockholm Univ, Roslagstullsbacken 23, SE-10691 Stockholm, Sweden..
Fysikum Stockholm Univ, Oskar Klein Ctr Cosmoparticle Phys, Roslagstullsbacken 21, SE-10961 Stockholm, Sweden..
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.ORCID iD: 0000-0003-1489-8512
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2018 (English)In: Physica Status Solidi. Rapid Research Letters, ISSN 1862-6254, E-ISSN 1862-6270, Vol. 12, no 11, article id 1800293Article in journal (Refereed) Published
Abstract [en]

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 toward lighter WIMPs, which are more difficult to probe experimentally. A detection of sub-GeV WIMPs will require the use of small gap materials in sensors. Using recent estimates of the WIMP mass, we identify the relevant target space toward small gap materials (100 to 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 () 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)center dot Br which exhibits a tiny gap of approximate to 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.

Place, publisher, year, edition, pages
WILEY-V C H VERLAG GMBH , 2018. Vol. 12, no 11, article id 1800293
Keywords [en]
BEDT-TTF, dark matter detection, Dirac materials, materials informatics, organic materials database
National Category
Materials Engineering
Identifiers
URN: urn:nbn:se:kth:diva-239810DOI: 10.1002/pssr.201800293ISI: 000450130300008Scopus ID: 2-s2.0-85053502622OAI: oai:DiVA.org:kth-239810DiVA, id: diva2:1275869
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QC 20190107

Available from: 2019-01-07 Created: 2019-01-07 Last updated: 2019-01-07Bibliographically approved

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Geilhufe, MatthiasOlsthoorn, BartKoski, TimoBalatsky, Alexander V.

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