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Title:An efficient computational framework for prediction of corrugation in twisted bilayer graphene
Author(s):Rakib, Tawfiqur
Advisor(s):Johnson, Harley T.
Contributor(s):Ertekin, Elif T
Department / Program:Mechanical Sci & Engineering
Discipline:Mechanical Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Graphene
twist
corrugation
moir\'e
superconductivity
Abstract:The discovery of unconventional superconductivity at a specific "magic" angle in twisted bilayer graphene (TBG) has stirred a lot of interest in the scientific community. When two graphene layers are placed on top of each other with a twist, a moir\'e pattern emerges. By controlling the period of the moir\'e in twisted bilayer graphene, we can tune the properties of TBG. Specifically, long periods of moir\'e in bilayer graphene have shown remarkable electronic properties. However, materials with large moir\'e periods are often difficult to study because of the expensive computational framework of electronic structure. Therefore, we develop a simple computational framework that can predict the corrugated structure of TBG of large periods in a computationally tractable way. From our density functional theory (DFT) simulations, we find that the structure of TBG becomes corrugated upon relaxation due to the change of interlayer distances in different stacking regions. The corrugation increases with decreasing twist angle in the TBG. Moreover, we also find that the AA region in the TBG shrinks and the AB region becomes larger at low twist angles (less than 1.5$^{\circ}$). Our framework is able to capture this phenomenon of shrinking of the AA region and map the corrugation for low twist angles with precision. With our framework, it would be possible to map the atomic coordinates of the corrugated structure of TBG which can help us to study different properties of low twist angle TBG more accurately. In this way, this framework may open the door to more tunable exotic properties in twisted bilayer graphene.
Issue Date:2020-12-10
Type:Thesis
URI:http://hdl.handle.net/2142/110400
Rights Information:© 2020 Tawfiqur Rakib
Date Available in IDEALS:2021-09-17
Date Deposited:2021-05


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