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On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets
Raman spectroscopy is one of the most common methods to characterize graphene-related 2D materials, providing information on a wide range of physical and chemical properties. Because of typical sample inhomogeneity, Raman spectra are acquired from several locations across a sample, and analysis is c...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Beilstein-Institut
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155622/ https://www.ncbi.nlm.nih.gov/pubmed/37152472 http://dx.doi.org/10.3762/bjnano.14.42 |
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author | Paton, Keith R Despotelis, Konstantinos Kumar, Naresh Turner, Piers Pollard, Andrew J |
author_facet | Paton, Keith R Despotelis, Konstantinos Kumar, Naresh Turner, Piers Pollard, Andrew J |
author_sort | Paton, Keith R |
collection | PubMed |
description | Raman spectroscopy is one of the most common methods to characterize graphene-related 2D materials, providing information on a wide range of physical and chemical properties. Because of typical sample inhomogeneity, Raman spectra are acquired from several locations across a sample, and analysis is carried out on the averaged spectrum from all locations. This is then used to characterize the “quality” of the graphene produced, in particular the level of exfoliation for top-down manufactured materials. However, these have generally been developed using samples prepared with careful separation of unexfoliated materials. In this work we assess these metrics when applied to non-ideal samples, where unexfoliated graphite has been deliberately added to the exfoliated material. We demonstrate that previously published metrics, when applied to averaged spectra, do not allow the presence of this unexfoliated material to be reliably detected. Furthermore, when a sufficiently large number of spectra are acquired, it is found that by processing and classifying individual spectra, rather than the averaged spectrum, it is possible to identify the presence of this material in the sample, although quantification of the amount remains approximate. We therefore recommend this approach as a robust methodology for reliable characterization of mass-produced graphene-related 2D materials using confocal Raman spectroscopy. |
format | Online Article Text |
id | pubmed-10155622 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Beilstein-Institut |
record_format | MEDLINE/PubMed |
spelling | pubmed-101556222023-05-04 On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets Paton, Keith R Despotelis, Konstantinos Kumar, Naresh Turner, Piers Pollard, Andrew J Beilstein J Nanotechnol Full Research Paper Raman spectroscopy is one of the most common methods to characterize graphene-related 2D materials, providing information on a wide range of physical and chemical properties. Because of typical sample inhomogeneity, Raman spectra are acquired from several locations across a sample, and analysis is carried out on the averaged spectrum from all locations. This is then used to characterize the “quality” of the graphene produced, in particular the level of exfoliation for top-down manufactured materials. However, these have generally been developed using samples prepared with careful separation of unexfoliated materials. In this work we assess these metrics when applied to non-ideal samples, where unexfoliated graphite has been deliberately added to the exfoliated material. We demonstrate that previously published metrics, when applied to averaged spectra, do not allow the presence of this unexfoliated material to be reliably detected. Furthermore, when a sufficiently large number of spectra are acquired, it is found that by processing and classifying individual spectra, rather than the averaged spectrum, it is possible to identify the presence of this material in the sample, although quantification of the amount remains approximate. We therefore recommend this approach as a robust methodology for reliable characterization of mass-produced graphene-related 2D materials using confocal Raman spectroscopy. Beilstein-Institut 2023-04-24 /pmc/articles/PMC10155622/ /pubmed/37152472 http://dx.doi.org/10.3762/bjnano.14.42 Text en Copyright © 2023, Paton et al. https://creativecommons.org/licenses/by/4.0/This is an open access article licensed under the terms of the Beilstein-Institut Open Access License Agreement (https://www.beilstein-journals.org/bjnano/terms/terms), which is identical to the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ). The reuse of material under this license requires that the author(s), source and license are credited. Third-party material in this article could be subject to other licenses (typically indicated in the credit line), and in this case, users are required to obtain permission from the license holder to reuse the material. |
spellingShingle | Full Research Paper Paton, Keith R Despotelis, Konstantinos Kumar, Naresh Turner, Piers Pollard, Andrew J On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets |
title | On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets |
title_full | On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets |
title_fullStr | On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets |
title_full_unstemmed | On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets |
title_short | On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets |
title_sort | on the use of raman spectroscopy to characterize mass-produced graphene nanoplatelets |
topic | Full Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155622/ https://www.ncbi.nlm.nih.gov/pubmed/37152472 http://dx.doi.org/10.3762/bjnano.14.42 |
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