2014•Nanoscale Research LettersOpen access

Probing substrate influence on graphene by analyzing Raman lineshapes

Chen-Han Huang, Hsing-Ying Lin, Cheng-Wen Huang, Yi-Min Liu, Fu‐Yu Shih, Weihua Wang, Hsiang‐Chen Chui

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Abstract

We provide a new approach to identify the substrate influence on graphene surface. Distinguishing the substrate influences or the doping effects of charged impurities on graphene can be realized by optically probing the graphene surfaces, included the suspended and supported graphene. In this work, the line scan of Raman spectroscopy was performed across the graphene surface on the ordered square hole. Then, the bandwidths of G-band and 2D-band were fitted into the Voigt profile, a convolution of Gaussian and Lorentzian profiles. The bandwidths of Lorentzian parts were kept as constant whether it is the suspended and supported graphene. For the Gaussian part, the suspended graphene exhibits much greater Gaussian bandwidths than those of the supported graphene. It reveals that the doping effect on supported graphene is stronger than that of suspended graphene. Compared with the previous studies, we also used the peak positions of G bands, and I2D/IG ratios to confirm that our method really works. For the suspended graphene, the peak positions of G band are downshifted with respect to supported graphene, and the I2D/IG ratios of suspended graphene are larger than those of supported graphene. With data fitting into Voigt profile, one can find out the information behind the lineshapes.

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We provide a new approach to identify the substrate influence on graphene surface. Distinguishing the substrate influences or the doping effects of charged impurities on graphene can be realized by optically probing the graphene surfaces, included the suspended and supported graphene. In this work, the line scan of Raman spectroscopy was performed across the graphene surface on the ordered square hole. Then, the bandwidths of G-band and 2D-band were fitted into the Voigt profile, a convolution of Gaussian and Lorentzian profiles. The bandwidths of Lorentzian parts were kept as constant whether it is the suspended and supported graphene. For the Gaussian part, the suspended graphene exhibits much greater Gaussian bandwidths than those of the supported graphene. It reveals that the doping effect on supported graphene is stronger than that of suspended graphene. Compared with the previous studies, we also used the peak positions of G bands, and I2D/IG ratios to confirm that our method really works. For the suspended graphene, the peak positions of G band are downshifted with respect to supported graphene, and the I2D/IG ratios of suspended graphene are larger than those of supported graphene. With data fitting into Voigt profile, one can find out the information behind the lineshapes.

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Available abstract

We provide a new approach to identify the substrate influence on graphene surface. Distinguishing the substrate influences or the doping effects of charged impurities on graphene can be realized by optically probing the graphene surfaces, included the suspended and supported graphene. In this work, the line scan of Raman spectroscopy was performed across the graphene surface on the ordered square hole. Then, the bandwidths of G-band and 2D-band were fitted into the Voigt profile, a convolution of Gaussian and Lorentzian profiles. The bandwidths of Lorentzian parts were kept as constant whether it is the suspended and supported graphene. For the Gaussian part, the suspended graphene exhibits much greater Gaussian bandwidths than those of the supported graphene. It reveals that the doping effect on supported graphene is stronger than that of suspended graphene. Compared with the previous studies, we also used the peak positions of G bands, and I2D/IG ratios to confirm that our method really works. For the suspended graphene, the peak positions of G band are downshifted with respect to supported graphene, and the I2D/IG ratios of suspended graphene are larger than those of supported graphene. With data fitting into Voigt profile, one can find out the information behind the lineshapes.

Key concepts: Graphene, Raman spectroscopy, Materials science, G band, Graphene nanoribbons, Substrate (aquarium), Voigt profile, Doping

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