Structural and electron diffraction scaling of twisted graphene bilayers

Structural and electron diffraction scaling of twisted graphene bilayers
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DOI:
10.1016/j.jmps.2017.12.005
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发表时间:
2018-03
影响因子:
5.3
通讯作者:
Kuan Zhang;E. Tadmor
Kuan Zhang;E. Tadmor
中科院分区:
工程技术2区
文献类型:
--
作者:
Kuan Zhang;E. Tadmor

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多尺度模拟被用来研究扭曲的石墨烯双层膜的结构弛豫和相关的电子衍射图案。初始扭曲形成不相称的莫尔图案,该图案松弛成相称的微结构,该微结构由围绕高能AA域的交替的低能AB域和BA域的重复图案组成。模拟结果表明,松弛机制涉及一个本地化的旋转和收缩的AA域的规模在两个制度与强加的扭曲。对于小的扭转角,局部旋转趋于恒定;对于大的扭转,旋转与之成线性比例。这种行为与莫尔图案尺寸随扭转角的逆比例有关,并使用线性弹性模型进行理论解释。通过对弛豫结构的模拟电子衍射分析,对结果进行了实验验证。一个复杂的电子衍射图案涉及的外观弱卫星峰预测为小扭曲制度。这种新的衍射图案解释使用的分析模型,其中的松弛运动学被描述为一个指数衰减(高斯)旋转场集中在AA域。角度相关的标度和衍射图案与实验观察定量一致。给出了高斯模型参数提取的Matlab程序。
Multiscale simulations are used to study the structural relaxation in twisted graphene bilayers and the associated electron diffraction patterns. The initial twist forms an incommensurate moiré pattern that relaxes to a commensurate microstructure comprised of a repeating pattern of alternating low-energy AB and BA domains surrounding a high-energy AA domain. The simulations show that the relaxation mechanism involves a localized rotation and shrinking of the AA domains that scales in two regimes with the imposed twist. For small twisting angles, the localized rotation tends to a constant; for large twist, the rotation scales linearly with it. This behavior is tied to the inverse scaling of the moiré pattern size with twist angle and is explained theoretically using a linear elasticity model. The results are validated experimentally through a simulated electron diffraction analysis of the relaxed structures. A complex electron diffraction pattern involving the appearance of weak satellite peaks is predicted for the small twist regime. This new diffraction pattern is explained using an analytical model in which the relaxation kinematics are described as an exponentially-decaying (Gaussian) rotation field centered on the AA domains. Both the angle-dependent scaling and diffraction patterns are in quantitative agreement with experimental observations. A Matlab program for extracting the Gaussian model parameters accompanies this paper.