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  Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing

Acosta, C. M., Ouyang, R., Fazzio, A., Scheffler, M., Ghiringhelli, L. M., & Carbogno, C. (in preparation). Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing.

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1805.10950.pdf (Preprint), 4MB
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 Urheber:
Acosta, Carlos Mera1, 2, Autor
Ouyang, Runhai1, Autor           
Fazzio, Adalberto2, 3, Autor
Scheffler, Matthias1, Autor           
Ghiringhelli, Luca M.1, Autor           
Carbogno, Christian1, Autor           
Affiliations:
1Theory, Fritz Haber Institute, Max Planck Society, ou_634547              
2Institute of Physics, University of Sao Paulo, CP 66318, 05315-970, Sao Paulo, SP, Brazil, ou_persistent22              
3Brazilian Nanotechnology National Laboratory, CP 6192, 13083-970, Campinas, SP, Brazil, ou_persistent22              

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Schlagwörter: Condensed Matter, Materials Science, cond-mat.mtrl-sci
 Zusammenfassung: Quantum spin-Hall insulators (QSHIs), i.e., two-dimensional topological insulators (TIs) with a symmetry-protected band inversion, have attracted considerable scientific interest in recent years. In this work, we have computed the topological Z2 invariant for 220 functionalized honeycomb lattices that are isoelectronic to functionalized graphene. Besides confirming the TI character of well-known materials such as functionalized stanene, our study identifies 45 yet unreported QSHIs. We applied a compressed-sensing approach to identify a physically meaningful descriptor for the Z2 invariant that only depends on the properties of the material's constituent atoms. This enables us to draw a map of materials, in which metals, trivial insulators, and QSHI form distinct regions. This analysis yields fundamental insights in the mechanisms driving topological transitions. The transferability of the identified model is explicitly demonstrated for an additional set of honeycomb lattices with different functionalizations that are not part of the original set of 220 graphene-type materials used to identify the descriptor. In this class, we predict 74 more novel QSHIs that have not been reported in literature yet.

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Sprache(n): eng - English
 Datum: 2018-05-28
 Publikationsstatus: Keine Angabe
 Seiten: 10
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 Identifikatoren: arXiv: 1805.10950
URI: http://arxiv.org/abs/1805.10950
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