Chemical Mapping of Graphene-Based Material with X-ray Photoelectron Spectroscopy (XPS) Using Principal Component Analysis (PCA)

Ayşegül Erdoğan; Merve Aktürk; Zekerya Dursun

Research Article

Grafen Temelli Malzemelerin PCA Kullanılarak XPS ile Kimyasal Haritalanması

Year 2019, Volume: 12 Issue: 2, 820 - 832, 31.08.2019

Ayşegül Erdoğan Merve Aktürk Zekerya Dursun

Abstract

Öz

XPS, malzemelerin yüzey
kimyasının karakterize edilmesinde yaygın olarak kullanılmaktadır. Kalitatif,
yarı kantitatif/kantitatif bilgilerin yanı sıra herhangi bir malzemenin
yüzeyindeki kimyasal fonksiyonel gruplar ve türleme hakkındaki bilgilere
ulaşmada önemli bir rol oynamaktadır. PCA, belirli bir veri setindeki
değişkenliğin analizidir. Örnekler ve değişkenler arasındaki ilişkileri
anlamak için en güçlü grafik araçlarını sağlamaktadır. İlk ana bileşen,
verilerdeki değişkenliğin mümkün olduğunca çoğunu oluşturur ve en büyük
özdeğere sahiptir. En önemli bilgileri elde etmek amacıyla, XPS tarafından
elde edilen büyük görüntü veri setlerini pca kullanarak analiz
edilebilmektedir. XPS verilerinden elde edilen bir alan taramasında PCA' nın
amacı, birbiri ile ilişkili ya da ilişkili olmayan görüntüleri bulmak ve bu
ilişkilerden sorumlu olan pikselleri görselleştirmektir/tanımlamaktır.
Görüntüler, bir görüntü-spektrum deneyinde bağlanma enerjisinin bir
fonksiyonu olarak elde edilir. Küçük alan spektrumları, tek bir piksel veya
bir piksel grubu ile bağlanma enerjisine karşı görüntü piksel yoğunluğunu
çizerek numunenin herhangi bir kısmından elde edilebilir. Bu çalışmada,
grafen bazlı malzeme, Brodie yöntemi ile grafitin oksidasyonu yoluyla
sentezlenmiştir. Daha sonra, spektral bilgiye dayalı olarak PCA ile kimyasal
haritalama oluşturulmuştur. Bu amaçla, XPS alan taraması gerçekleştirilmiş ve
sentezlenen grafen bazlı malzeme yüzeyindeki homojensizlikleri göstermek için
veri setlerine PCA uygulanmıştır.

Keywords

Kimyasal haritalama, X-Işını Fotoelektron Spketroskopisi, temel bileşenler analizi, grafen

References

Abdi, H., & Williams, L. J. (2010). Principal component analysis. Wiley interdisciplinary reviews: computational statistics, 2(4), 433-459.
Artyushkova, K., & Fulghum, J. E. (2001). Identification of chemical components in XPS spectra and images using multivariate statistical analysis methods. Journal of Electron Spectroscopy and Related Phenomena, 121(1), 33-55.
Artyushkova, K., & Fulghum, J. E. (2002). Multivariate image analysis methods applied to XPS imaging data sets. Surface and interface analysis, 33(3), 185-195. Artyushkova, K., & Fulghum, J. E. (2004). Mathematical topographical correction of XPS images using multivariate statistical methods. Surface and interface analysis, 36(9), 1304-1313.
Barlow, A. J., Scott, O., Sano, N., & Cumpson, P. J. (2015). Multivariate Auger Feature Imaging (MAFI)–a new approach towards chemical state identification of novel carbons in XPS imaging. Surface and interface analysis, 47(2), 173-175.
Béchu, S., Richard‐Plouet, M., Fernandez, V., Walton, J., & Fairley, N. (2016). Developments in numerical treatments for large data sets of XPS images. Surface and interface analysis.
Briggs, D., & Grant, J. T. (2003). Surface analysis by Auger and X-ray photoelectron spectroscopy: IM publications.
Brodie, B. C. (1859). On the atomic weight of graphite. Philosophical Transactions of the Royal Society of London, 149, 249-259.
Cumpson, P. J., Fletcher, I. W., Burnett, R., Sano, N., Barlow, A. J., Portoles, J. F., . . . Kiang, A. S. H. (2016). Multispectral optical imaging combined in situ with XPS or ToFSIMS and principal component analysis. Surface and interface analysis, 48(13), 1370-1378.
Dreyer, D. R., Park, S., Bielawski, C. W., & Ruoff, R. S. (2010). The chemistry of graphene oxide. Chemical Society Reviews, 39(1), 228-240.
Gurker, N., Ebel, M. F., & Ebel, H. (1983). Imaging XPS—A new technique, I—principles. Surface and interface analysis, 5(1), 13-19.
Hofmann, S. (1986). Practical surface analysis: state of the art and recent developments in AES, XPS, ISS and SIMS. Surface and interface analysis, 9(1), 3-20.
Kalegowda, Y., & Harmer, S. L. (2012). Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu–Fe sulfides. Analytical chemistry, 84(6), 2754-2760.
Lee, J. L., & Gilmore, I. S. (2009). The application of multivariate data analysis techniques in surface analysis Surface Analysis–The Principal Techniques.Sastry, M. (1997). Application of principal component analysis to x-ray photoelectron spectroscopy—the role of noise in the spectra. Journal of Electron Spectroscopy and Related Phenomena, 83(2), 143-150.
Vickerman, J. C., & Gilmore, I. (2011). Surface analysis: the principal techniques: John Wiley & Sons.
Wise, B. M., & Geladi, P. (2000). A brief introduction to multivariate image analysis (MIA). Eigenvector Research, Inc., http://www. eigenvector. com/Docs/MIA_Intro. pdf.
Zhang, L., Henson, M. J., & Sekulic, S. S. (2005). Multivariate data analysis for Raman imaging of a model pharmaceutical tablet. Analytica Chimica Acta, 545(2), 262-278.

Chemical Mapping of Graphene-Based Material with X-ray Photoelectron Spectroscopy (XPS) Using Principal Component Analysis (PCA)

Year 2019, Volume: 12 Issue: 2, 820 - 832, 31.08.2019

Ayşegül Erdoğan Merve Aktürk Zekerya Dursun

Abstract

XPS has been extensively
used to characterize the surface chemistry of materials. It plays a unique role
in giving access to qualitative, semi-quantitative/quantitative information as
well as speciation and the presence of chemical functional groups on the
surface of any material. PCA is the analysis of variability in a particular set
of data. The first principal component accounts for as much of the variability
in the data as possible and has the largest eigenvalue. Large image data sets
obtained by XPS can be analyzed using PCA in order to extract the most
significant information. The goal of PCA in an area scan of XPS is to find
images which are correlated or anti-correlated. Images are acquired as a
function of binding energy in an images-to-spectra experiment. Small area
spectra can be obtained from any part of the sample by plotting image pixel
intensity for a single pixel or a group of pixels versus binding energy. In the
present study, the graphene-based material was synthesized via oxidation of
graphite by Brodie Method. Then, chemical mapping has been produced with PCA on
the basis of spectral information. For this purpose, XPS area scan has been
performed and then the data sets were subjected to PCA in order to present the
compositional inhomogeneities on the surface of synthesized graphene-based
material.

Keywords

Chemical mapping, X-ray photoelectron spectroscopy, principal component analysis, graphene

References

Abdi, H., & Williams, L. J. (2010). Principal component analysis. Wiley interdisciplinary reviews: computational statistics, 2(4), 433-459.
Artyushkova, K., & Fulghum, J. E. (2001). Identification of chemical components in XPS spectra and images using multivariate statistical analysis methods. Journal of Electron Spectroscopy and Related Phenomena, 121(1), 33-55.
Artyushkova, K., & Fulghum, J. E. (2002). Multivariate image analysis methods applied to XPS imaging data sets. Surface and interface analysis, 33(3), 185-195. Artyushkova, K., & Fulghum, J. E. (2004). Mathematical topographical correction of XPS images using multivariate statistical methods. Surface and interface analysis, 36(9), 1304-1313.
Barlow, A. J., Scott, O., Sano, N., & Cumpson, P. J. (2015). Multivariate Auger Feature Imaging (MAFI)–a new approach towards chemical state identification of novel carbons in XPS imaging. Surface and interface analysis, 47(2), 173-175.
Béchu, S., Richard‐Plouet, M., Fernandez, V., Walton, J., & Fairley, N. (2016). Developments in numerical treatments for large data sets of XPS images. Surface and interface analysis.
Briggs, D., & Grant, J. T. (2003). Surface analysis by Auger and X-ray photoelectron spectroscopy: IM publications.
Brodie, B. C. (1859). On the atomic weight of graphite. Philosophical Transactions of the Royal Society of London, 149, 249-259.
Cumpson, P. J., Fletcher, I. W., Burnett, R., Sano, N., Barlow, A. J., Portoles, J. F., . . . Kiang, A. S. H. (2016). Multispectral optical imaging combined in situ with XPS or ToFSIMS and principal component analysis. Surface and interface analysis, 48(13), 1370-1378.
Dreyer, D. R., Park, S., Bielawski, C. W., & Ruoff, R. S. (2010). The chemistry of graphene oxide. Chemical Society Reviews, 39(1), 228-240.
Gurker, N., Ebel, M. F., & Ebel, H. (1983). Imaging XPS—A new technique, I—principles. Surface and interface analysis, 5(1), 13-19.
Hofmann, S. (1986). Practical surface analysis: state of the art and recent developments in AES, XPS, ISS and SIMS. Surface and interface analysis, 9(1), 3-20.
Kalegowda, Y., & Harmer, S. L. (2012). Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu–Fe sulfides. Analytical chemistry, 84(6), 2754-2760.
Lee, J. L., & Gilmore, I. S. (2009). The application of multivariate data analysis techniques in surface analysis Surface Analysis–The Principal Techniques.Sastry, M. (1997). Application of principal component analysis to x-ray photoelectron spectroscopy—the role of noise in the spectra. Journal of Electron Spectroscopy and Related Phenomena, 83(2), 143-150.
Vickerman, J. C., & Gilmore, I. (2011). Surface analysis: the principal techniques: John Wiley & Sons.
Wise, B. M., & Geladi, P. (2000). A brief introduction to multivariate image analysis (MIA). Eigenvector Research, Inc., http://www. eigenvector. com/Docs/MIA_Intro. pdf.
Zhang, L., Henson, M. J., & Sekulic, S. S. (2005). Multivariate data analysis for Raman imaging of a model pharmaceutical tablet. Analytica Chimica Acta, 545(2), 262-278.

There are 16 citations in total.

Details

Primary Language	English
Subjects	Engineering
Journal Section	Makaleler
Authors	Ayşegül Erdoğan 0000-0002-3174-7970 Merve Aktürk This is me Zekerya Dursun
Publication Date	August 31, 2019
Published in Issue	Year 2019 Volume: 12 Issue: 2

Cite

APA	Erdoğan, A., Aktürk, M., & Dursun, Z. (2019). Chemical Mapping of Graphene-Based Material with X-ray Photoelectron Spectroscopy (XPS) Using Principal Component Analysis (PCA). Erzincan University Journal of Science and Technology, 12(2), 820-832.