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Recognition of Spatial Distribution of CNT and Graphene in Hybrid Structure by Mapping with Coherent Anti-Stokes Raman Microscopy
Nanoscale Research Letters ( IF 5.418 ) Pub Date : 2020-02-07 , DOI: 10.1186/s11671-020-3264-8
Alesia Paddubskaya , Danielis Rutkauskas , Renata Karpicz , Galina Dovbeshko , Nadezhda Nebogatikova , Irina Antonova , Andrej Dementjev

Abstract

The shape of coherent anti-Stokes Raman scattering (CARS) spectral line depends on the ratio of the vibrational and electronic contributions to the third-order susceptibility of the material. The G-mode (1590 cm−1) of graphene and carbon nanotubes (CNTs) exhibits opposite features in the CARS spectrum, showing “dip” and “peak,” respectively. Here, we consider the CARS spectra of graphene and carbon nanotubes in terms of Fano formalism describing the line shapes of CARS resonances. We show that imaging at only 1590 cm−1 is not sufficient to separate the constituents of a composite material consisting of both graphene and CNTs. We propose an algorithm to map the graphene and CNTs in a composite material.



中文翻译:

相干反斯托克斯拉曼显微成像法识别杂化结构中碳纳米管和石墨烯的空间分布

摘要

相干抗斯托克斯拉曼散射(CARS)谱线的形状取决于振动和电子贡献与材料三阶磁化率的比值。石墨烯和碳纳米管(CNT)的G模式(1590 cm -1)在CARS光谱中表现出相反的特征,分别显示“浸入”和“峰值”。在这里,我们根据Fano形式主义描述石墨烯和碳纳米管的CARS光谱,描述了CARS共振的线形。我们显示,仅在1590 cm -1处成像不足以分离由石墨烯和CNT组成的复合材料的成分。我们提出了一种在复合材料中映射石墨烯和碳纳米管的算法。

更新日期:2020-02-07
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