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Layer number identification of CVD-grown multilayer graphene using Si peak analysis
Since the successful exfoliation of graphene, various methodologies have been developed to identify the number of layers of exfoliated graphene. The optical contrast, Raman G-peak intensity, and 2D-peak line-shape are currently widely used as the first level of inspection for graphene samples. Altho...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766578/ https://www.ncbi.nlm.nih.gov/pubmed/29330376 http://dx.doi.org/10.1038/s41598-017-19084-1 |
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author | No, You-Shin Choi, Hong Kyw Kim, Jin-Soo Kim, Hakseong Yu, Young-Jun Choi, Choon-Gi Choi, Jin Sik |
author_facet | No, You-Shin Choi, Hong Kyw Kim, Jin-Soo Kim, Hakseong Yu, Young-Jun Choi, Choon-Gi Choi, Jin Sik |
author_sort | No, You-Shin |
collection | PubMed |
description | Since the successful exfoliation of graphene, various methodologies have been developed to identify the number of layers of exfoliated graphene. The optical contrast, Raman G-peak intensity, and 2D-peak line-shape are currently widely used as the first level of inspection for graphene samples. Although the combination analysis of G- and 2D-peaks is powerful for exfoliated graphene samples, its use is limited in chemical vapor deposition (CVD)-grown graphene because CVD-grown graphene consists of various domains with randomly rotated crystallographic axes between layers, which makes the G- and 2D-peaks analysis difficult for use in number identification. We report herein that the Raman Si-peak intensity can be a universal measure for the number identification of multilayered graphene. We synthesized a few-layered graphene via the CVD method and performed Raman spectroscopy. Moreover, we measured the Si-peak intensities from various individual graphene domains and correlated them with the corresponding layer numbers. We then compared the normalized Si-peak intensity of the CVD-grown multilayer graphene with the exfoliated multilayer graphene as a reference and successfully identified the layer number of the CVD-grown graphene. We believe that this Si-peak analysis can be further applied to various 2-dimensional (2D) materials prepared by both exfoliation and chemical growth. |
format | Online Article Text |
id | pubmed-5766578 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57665782018-01-17 Layer number identification of CVD-grown multilayer graphene using Si peak analysis No, You-Shin Choi, Hong Kyw Kim, Jin-Soo Kim, Hakseong Yu, Young-Jun Choi, Choon-Gi Choi, Jin Sik Sci Rep Article Since the successful exfoliation of graphene, various methodologies have been developed to identify the number of layers of exfoliated graphene. The optical contrast, Raman G-peak intensity, and 2D-peak line-shape are currently widely used as the first level of inspection for graphene samples. Although the combination analysis of G- and 2D-peaks is powerful for exfoliated graphene samples, its use is limited in chemical vapor deposition (CVD)-grown graphene because CVD-grown graphene consists of various domains with randomly rotated crystallographic axes between layers, which makes the G- and 2D-peaks analysis difficult for use in number identification. We report herein that the Raman Si-peak intensity can be a universal measure for the number identification of multilayered graphene. We synthesized a few-layered graphene via the CVD method and performed Raman spectroscopy. Moreover, we measured the Si-peak intensities from various individual graphene domains and correlated them with the corresponding layer numbers. We then compared the normalized Si-peak intensity of the CVD-grown multilayer graphene with the exfoliated multilayer graphene as a reference and successfully identified the layer number of the CVD-grown graphene. We believe that this Si-peak analysis can be further applied to various 2-dimensional (2D) materials prepared by both exfoliation and chemical growth. Nature Publishing Group UK 2018-01-12 /pmc/articles/PMC5766578/ /pubmed/29330376 http://dx.doi.org/10.1038/s41598-017-19084-1 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article No, You-Shin Choi, Hong Kyw Kim, Jin-Soo Kim, Hakseong Yu, Young-Jun Choi, Choon-Gi Choi, Jin Sik Layer number identification of CVD-grown multilayer graphene using Si peak analysis |
title | Layer number identification of CVD-grown multilayer graphene using Si peak analysis |
title_full | Layer number identification of CVD-grown multilayer graphene using Si peak analysis |
title_fullStr | Layer number identification of CVD-grown multilayer graphene using Si peak analysis |
title_full_unstemmed | Layer number identification of CVD-grown multilayer graphene using Si peak analysis |
title_short | Layer number identification of CVD-grown multilayer graphene using Si peak analysis |
title_sort | layer number identification of cvd-grown multilayer graphene using si peak analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766578/ https://www.ncbi.nlm.nih.gov/pubmed/29330376 http://dx.doi.org/10.1038/s41598-017-19084-1 |
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