Applications of Raman spectroscopy in graphene-related materials and the development of parameterized PCA for large-scale data analysis

被引：35

作者：

Elias Campos, Joao Luiz ^{[1
]}

Miranda, Hudson ^{[2
]}

Rabelo, Cassiano ^{[2
]}

Sandoz-Rosado, Emil ^{[3
]}

Pandey, Sugandha ^{[1
]}

Riikonen, Juha ^{[4
]}

Cano-Marquez, Abraham G. ^{[5
]}

Jorio, Ado ^{[1
,2
]}

机构：

[1] Univ Fed Minas Gerais, Dept Fis, BR-30270970 Belo Horizonte, MG, Brazil

[2] Univ Fed Minas Gerais, Programa Posgrad Engn Eletr, BR-30270970 Belo Horizonte, MG, Brazil

[3] US Army Res Lab, Aberdeen Proving Ground, MD 21005 USA

[4] Aalto Univ, Dept Micro & Nanosci, Espoo 02150, Finland

[5] Ctr Invest Mat Avanzados, Unidad Monterrey, Apodaca 66628, NL, Mexico

来源：

JOURNAL OF RAMAN SPECTROSCOPY | 2018年 / 49卷 / 01期

关键词：

graphene; principal component analysis; applications; large-data analysis; carbon nanomaterial; CARBON; TRANSITION;

D O I：

10.1002/jrs.5225

中图分类号：

O433 [光谱学];

学科分类号：

0703 ; 070302 ;

摘要：

A methodology for the structural analysis of graphene-related materials using parameterized principal component analysis (PCA), ideal for large-scale data treatment, is introduced. First, we review different aspects of Raman spectroscopy for structural and functional characterization of sp(2)-bonded carbon materials, which are important for understanding the problem. The parameterized PCA is then introduced and applied to 2 different scenarios: to identify different sp(2) carbon structures and to identify graphene samples with different numbers of layers. Automating these Raman spectroscopy analysis techniques is desired for large-scale industrial applications. Copyright (c) 2017 John Wiley & Sons, Ltd.

引用

页码：54 / 65

页数：12

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