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Free surfaces recast superconductivity in few-monolayer MgB2: Combined first-principles and ARPES demonstration
Univ Antwerp, Dept Phys, Groenenborgerlaan 171, B-2020 Antwerp, Belgium.
Univ Groningen, Zernike Inst Adv Mat, Nijenborgh 4, NL-9747 AG Groningen, Netherlands.; Elettra Sincrotrone Trieste, Str Statale 14 Km 163-5, I-34149 Trieste, Italy.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Materials Theory.
Univ Groningen, Zernike Inst Adv Mat, Nijenborgh 4, NL-9747 AG Groningen, Netherlands.
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2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, no 1, article id 14458Article in journal (Refereed) Published
Abstract [en]

Two-dimensional materials are known to harbour properties very different from those of their bulk counterparts. Recent years have seen the rise of atomically thin superconductors, with a caveat that superconductivity is strongly depleted unless enhanced by specific substrates, intercalants or adatoms. Surprisingly, the role in superconductivity of electronic states originating from simple free surfaces of two-dimensional materials has remained elusive to date. Here, based on first-principles calculations, anisotropic Eliashberg theory, and angle-resolved photoemission spectroscopy (ARPES), we show that surface states in few-monolayer MgB2 make a major contribution to the superconducting gap spectrum and density of states, clearly distinct from the widely known, bulk-like σ- and π-gaps. As a proof of principle, we predict and measure the gap opening on the magnesium-based surface band up to a critical temperature as high as ~30 K for merely six monolayers thick MgB2. These findings establish free surfaces as an unavoidable ingredient in understanding and further tailoring of superconductivity in atomically thin materials.

Place, publisher, year, edition, pages
2017. Vol. 7, no 1, article id 14458
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Condensed Matter Physics
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URN: urn:nbn:se:uu:diva-332816DOI: 10.1038/s41598-017-13913-zISI: 000414231000059PubMedID: 29089566OAI: oai:DiVA.org:uu-332816DiVA, id: diva2:1154228
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Swedish Research CouncilSwedish National Infrastructure for Computing (SNIC)Available from: 2017-11-01 Created: 2017-11-01 Last updated: 2018-02-08Bibliographically approved

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