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arXiv 2406.05643cond-mat.mes-hallcond-mat.other
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从Floquet准能谱预测锯齿形石墨烯纳米带边缘局域单空位缺陷

Predicting edge-localized monovacancy defects in zigzag graphene nanoribbons from Floquet quasienergy spectrum

Gulshan Kumar, Shashikant Kumar, Ajay Kumar, Prakash Parida

AI总结:

本文利用Floquet-Bloch理论,通过分析圆偏振光下Floquet边缘态取向和费米能级附近新Dirac点,预测锯齿形石墨烯纳米带边缘单空位缺陷的位置,并可推广到其他空位缺陷。

摘要:

在这项工作中,我们提出一个理论框架,旨在利用Floquet-Bloch形式体系预测锯齿形石墨烯纳米带(ZGNRs)边缘单空位缺陷的位置,该预测可通过时间分辨和角分辨光电子能谱(tr-ARPES)进行实验观测。我们的方法包括深入研究在频率范围内不同偏振光影响下的Floquet准能带谱。特别是在频率与系统带宽相当、圆偏振光照射的条件下,我们的研究结果表明,这是一种有前景的方法,可用于定位任一边缘的单空位缺陷;而从含单空位缺陷的ZGNRs的ARPES谱中预测这一位置被证明是相当困难的。这一结果是通过分析Floquet边缘态的取向以及费米能级附近新出现的Dirac点实现的。这些引人注目的特性在实际应用中的价值凸显了我们理论框架的重要性和针对性,为进一步探索和实际应用铺平了道路。我们采用Floquet形式体系的方法并不局限于单空位型缺陷,而是可以扩展到涵盖各种类型的空位缺陷。

英文摘要:

In this work, we prescribe a theoretical framework aiming at predicting the position of monovacancy defects at the edges of zigzag graphene nanoribbons (ZGNRs) using Floquet-Bloch formalism, which can be experimentally observed through time- and angle-resolved photoemission spectroscopy (tr-ARPES). Our methodology involves an in-depth investigation of the Floquet quasienergy band spectrum influenced by light with varying polarization across a range of frequencies. Particularly under the influence of circularly polarized light with a frequency comparable to the bandwidth of the system, our findings suggest a promising approach for locating monovacancy defects at either edge, a challenge that proves intricate to predict from the ARPES spectrum of ZGNRs with monovacancy defects. This has been achieved by analyzing the orientation of the Floquet edge state and the appearance of new Dirac points in the vicinity of the Fermi level. The real-world applications of these captivating characteristics underscore the importance and pertinence of our theoretical framework, paving the way for additional exploration and practical use. Our approach, employing the Floquet formalism, is not limited to monovacancy-type defects; rather, it can be expanded to encompass various types of vacancy defects.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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