Publication
Title
Tight-binding description of intrinsic superconducting correlations in multilayer graphene
Author
Abstract
Using highly efficient GPU-based simulations of the tight-binding Bogoliubov-de Gennes equations we solve self-consistently for the pair correlation in rhombohedral (ABC) and Bernal (ABA) multilayer graphene by considering a finite intrinsic s-wave pairing potential. We find that the two different stacking configurations have opposite bulk/surface behavior for the order parameter. Surface superconductivity is robust for ABC stacked multilayer graphene even at very low pairing potentials for which the bulk order parameter vanishes, in agreement with a recent analytical approach. In contrast, for Bernal stacked multilayer graphene, we find that the order parameter is always suppressed at the surface and that there exists a critical value for the pairing potential below which no superconducting order is achieved. We considered different doping scenarios and find that homogeneous doping strongly suppresses surface superconductivity while nonhomogeneous field-induced doping has a much weaker effect on the superconducting order parameter. For multilayer structures with hybrid stacking (ABC and ABA) we find that when the thickness of each region is small (few layers), high-temperature surface superconductivity survives throughout the bulk due to the proximity effect between ABC/ABA interfaces where the order parameter is enhanced. DOI: 10.1103/PhysRevB.87.134509
Language
English
Source (journal)
Physical review : B : condensed matter and materials physics. - Lancaster, Pa, 1998 - 2015
Publication
Lancaster, Pa : 2013
ISSN
1098-0121 [print]
1550-235X [online]
Volume/pages
87:13(2013), p. 1-7
Article Reference
134509
ISI
000317390000006
Medium
E-only publicatie
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
[E?say:metaLocaldata.cgzprojectinf]
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 07.06.2013
Last edited 01.11.2017
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